Martijn Wieling

Martijn Wieling is Professor by special appointment of Low Saxon / Groningen Language and Culture at the Center for Groningen Language and Culture and an Associate Professor at the University of Groningen. In addition, he is Affiliated Scientist at Haskins Laboratories. His research focuses on investigating language variation and change quantitatively, with a specific focus on the Low Saxon language. He uses both large digital corpora of text and speech, as well as experimental approaches to assess differences in the movement of the tongue and lips during speech. More information about the research conducted in his group can be found on the website of the Speech Lab Groningen. Since 2019, he is a member of the Global Young Academy.

Academic positions

  • Present 2018

    Professor by special appointment of Low Saxon / Groningen Language and Culture

    Center for Groningen Language and Culture

  • Present 2018

    Associate Professor

    University of Groningen, Department of Information Science

  • 2018 2015

    Assistant Professor (with tenure)

    University of Groningen, Department of Information Science

  • 2015 2013

    Post-doctoral researcher (NWO Veni)

    University of Groningen, Department of Information Science

  • 2013 2012

    Post-doctoral researcher (NWO Rubicon)

    University of Tübingen, Department of Quantitative Linguistics

Education & Training

  • Ph.D. 2012

    Ph.D. in Linguistics (cum laude)

    University of Groningen, Faculty of Arts

  • M.Sc.2007

    Master (research) of Science in Behavioural and Cognitive Neurosciences (cum laude)

    University of Groningen, Faculty of Science and Engineering

  • M.Sc.2007

    Master of Science in Computing Science
    (cum laude)

    University of Groningen, Faculty of Science and Engineering

  • B.Sc.2005

    Bachelor of Science in Computing Science
    (cum laude)

    University of Groningen, Faculty of Science and Engineering

Honors, Awards and Grants (>€25,000)

  • 2019-2024
    NWO PhD in the Humanities Grant (€ 250,000)
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    This five-year research grant was awarded to Wieling and PhD student Teja Rebernik by the Netherlands Organisation for Scientific Research (NWO) for their project "Speech planning and monitoring in Parkinson's disease".

  • 2019-2023
    Google Community grant: Van Old noar Jong
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    In this Google-funded project, Wieling and his colleagues will develop a game to teach aspects of the Groningen dialects to primary school children.

  • GYA
    Member (2019) of the Global Young Academy
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    Wieling was selected as one (out of 600+ applications) of the 43 new members of the Global Young Academy (DJA) in May 2019 for a period of five years. The Global Young Academy gives a voice to young scientists around the world. To realise this vision, the GYA develops, connects, and mobilises young talent from six continents. Moreover, the GYA empowers young researchers to lead international, interdisciplinary, and inter-generational dialogue with the goal to make global decision making evidence-based and inclusive.

  • EYRA
    European Young Research Award (2016)
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    In 2016, Wieling was awarded the European Young Research Award for post-doctoral researchers. This prestigious award is granted every two years to researchers demonstrating outstanding research performance and leadership. It aims to inspire early stage researchers to incorporate a European dimension and perspective into their research. Wieling was the first awardee from the Humanities.
  • YAG
    Founding Member of the Young Academy Groningen (2016)
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    In 2016, Wieling was selected as one of the 18 founding members of the Young Academy of Groningen for a period of five years. The Young Academy Groningen is a club for the University of Groningen’s most talented, enthusiastic and ambitious young researchers. Members come from all fields and disciplines and have a passion for science and an interest in matters concerning science policy, science and society, leadership and career development.

  • DJA
    Member (2015) and vice-chairman (2018) of De Jonge Akademie
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    Wieling was selected as one of the youngest members of De Jonge Akademie (DJA) of the Royal Netherlands Academy of Arts and Sciences (KNAW) in April 2015 for a period of five years. In 2018, Wieling was elected as vice-chairman of De Jonge Akademie for a period of two years.The Young Academy is a dynamic and innovative group of 50 top young scientists and scholars with outspoken views about science and scholarship and the related policy. The Young Academy organises inspiring activities for various target groups focusing on interdisciplinarity, science policy, and the interface between science and society.

  • YSP
    Lisa Lena Opas-Hänninen Young Scholar Prize (2014)
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    At the Methods in Dialectology XV conference, Wieling was awarded the Lisa Lena Opas-Hänninen Young Scholar Prize for his poster presentation on Validating and using the PMI-based Levenshtein distance as a measure of foreign accent strength.
  • 2018-2019
    CIT Data Science Project Grant (€ 35,000; co-PI: Dr Nanna Hilton)
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    This one-year data science grant was awarded to Wieling and Hilton by the Centre for Information Technology of the University of Groningen for their project "Automatic recognition of Frisian speakers: Using computers to discriminate the Frisian accent and voice".
  • 2017-2021
    YAG Interdisciplinary PhD Grant (€ 120,000; co-PI: Prof. Michel Vols)
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    Together with Prof. Michel Vols, Wieling was awarded one of the three yearly interdisciplinary Young Academy of Groningen PhD grants for a project with the goal of automatically predicting court judgments.
  • 2017-2018
    Digital Humanities Explored Project Grant (€ 50,000)
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    This one-year data science grant was awarded to Wieling by the Centre for Digital Humanities of the University of Groningen for his project "Identifying Dutch accents automatically".
  • 2016-2017
    VIVIS Research Grant (€ 50,000)
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    This one-year research grant was awarded to Wieling by the Vereniging van Instellingen voor mensen met een VISuele beperking for his project "Automatic speech recognition for congenitally blind speakers".
  • 2013-2017
    NWO Veni Grant (€ 250,000)
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    This four-year research grant was awarded to Wieling by the Netherlands Organisation for Scientific Research (NWO) for his project "Improving speech learning models and English pronunciation with articulography". Only 15.5% of the submitted project proposals were granted.

  • 2012-2013
    NWO Rubicon Grant (€ 60,000)
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    This one-year research grant was awarded to Wieling by the Netherlands Organisation for Scientific Research (NWO) for his project "Investigating language variation physically". Only 12% of the submitted project proposals were granted.

Research

Research Summary

My research generally focuses on quantitatively investigating patterns in language variation and change. While I mostly investigate dialect variation, I also study the pronunciation of second language learners, congenitally blind speakers, or speakers with dysarthria (such as Parkinson's disease). Besides investigating pronunciation, I am interested in identifying patterns in large, digitally available corpora of text. For example, in collaboration with the law department, we are currently investigating how we may predict court judgments on the basis of various legal and linguistic characteristics of the court transcripts. This project also emphasizes the interdisciplinary and collaborative nature of my research (see also projects, below).

For investigating patterns in speech, I generally take two approaches. The first approach is to analyze phonetically transcribed data using new quantitative, dialectometric techniques (see publications in Language, Journal of Phonetics, Annual Review of Linguistics, Language Dynamics and Change and PLOS ONE). The second approach is to track the movement of speakers' tongue and lips using (e.g.,) electromagnetic articulography (see several publications in Journal of Phonetics, and Journal of the Acoustical Society of America).

In terms of techniques, I am frequently using (and teaching courses about) generalized additive modeling, a flexible non-linear regression technique which can be used to model the influence of geography on dialect variation, but also to model time series data (such as collected using articulography, eye-tracking or EEG experiments). See this extensive tutorial (published in Journal of Phonetics), but also publications in Language, Journal of Phonetics and PLOS ONE. More information about my research can be foun on the Speech Lab Groningen website.

Research projects

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    Speech planning and monitoring in Parkinson's disease

    (2019 - 2024)

    (PhD student: Teja Rebernik, Co-supervisors: Roel Jonkers and Aude Noiray)

    Despite doing it almost without effort, speaking is a highly complex task requiring precisely timed and linguistically driven coordination of the lungs, vocal folds and speech articulators (e.g. lips, tongue). This process, speech motor control, relies on both feedforward (pre planned movements based on stored movement representations drawn from past experiences) and feedback (monitoring sensory input relative to what is expected) control mechanisms. Research suggests that these mechanisms may be impaired in Parkinson’s disease (PD) patients. However, current findings have resulted from studies with small samples and heterogeneous PD groups.

    The central aim of this project is to identify which speech control mechanisms in PD patients are impaired and to what extent by comparing newly diagnosed PD patients, advanced stage PD patients, and healthy adults. Specifically, we will investigate how participants cope with feedback perturbations in speech, by measuring both the resulting acoustic speech signal and the underlying speech motor articulation using electromagnetic articulography and ultrasound tongue imaging. To assess whether the potential impairments of the feedback and feedforward system are speech-specific or more general (as PD is a movement disorder), we will also conduct feedback perturbation experiments in non-speech motor movement tasks.

    The innovative combination of these methods will enable us to identify whether and how impairments of speech planning and monitoring are related to the progression of PD. Furthermore, the extent to which PD patients cope with feedback perturbations compared to healthy adults may potentially serve as a diagnostic marker for the disease. This would be highly relevant in our aging society.

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    Van Old noar Jong

    (2019 - 2023)

    (PhD student: Martijn Bartelds)

    In this Google-funded project, we will develop community-specific applications to teach the local Groningen variety to primary school children. This project originated through a collaboration with Dorpsbelangen Zandeweer, Eppenhuizen en Doodstil. More information about this project can be found on this webpage.

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    Speech development in children with Duchenne muscular dystrophy

    (2019 - 2020)

    (Research assistant: Nora Jamoulle, Collaborators: Annemieke Aartsma-Rus, Aude Noiray, Erik Niks, Jos Hendriksen)

    In this project we aim to investigate if the speech (articulation) of young children with DMD differs from that of healthy children and if we may use these potential differences in early detection of DMD and to improve the pronunciation of older DMD patients who develop speech problems. This project is funded by the De Jonge Akademie.

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    Automatic rating and recognition of Groningen speakers

    (2019 - 2023)

    (PhD student: Martijn Bartelds, Co-supervisor: Nanna Hilton)

    In this project we aim to investigate (using a data-driven approach) how pronunciation variation in the province of Groningen and the Low Saxon language area is distributed geographically and how it has changed over time. In addition, we will investigate if it is possible to automatically rate how similar someone's pronunciation is to a specific regional target pronunciation. Finally, we aim to identify how many people speak a dialect and if this affects cognition. This project is funded by both the Center for Groningen Language and Culture, the Faculty of Arts of the University of Groningen and the Centre for Digital Humanities of the University of Groningen.

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    Automatic detection of linguistic patterns in legal big data

    (2017 - 2021)

    (PhD student: Masha Medvedeva, Co-PI: Michel Vols)

    Law is everywhere: almost every human activity is regulated. Buying a sandwich, renting an apartment or going to a hospital, all these activities involve legal rules and consequences. For a stable and sustainable society it is essential that its laws are predictable. People need to know what a legal rule means and what likely outcome a potential court case will have. Authorities have tried to improve the law's predictability and transparency by publishing court judgments. For decades, summaries of judgments were published in written journals, which were not easily accessible for the public. Nowadays, courts publish their judgments online. For example, approximately 370,000 individual court judgments can be found on the website of the Dutch judiciary (www.rechtspraak.nl). Similarly, another 52,000 court judgments are published online by the European Court of Human Rights (http://hudoc.echr.coe.int). Each of these judgments contains a detailed and rich description of the facts, procedure, reasoning of the parties and outcome of the case. Of course, public availability of case law will help to improve predictability and transparency, but to analyse hundreds of thousands of legal documents, we need other approaches than the traditional and labour-intensive 'doctrinal analysis' (i.e. close reading of a single or a small number of judgments) conducted by legal researchers.

    The goal of this PhD project is therefore to combine two distinctly separate disciplines, law and computational linguistics, in developing and evaluating quantitative, computational approaches to improve the predictability and transparency of the law. Techniques from computational linguistics would (for example) enable the automatic extraction, syntactic and semantic analysis of the judgment texts. The extracted features may be used in quantitative analyses identifying common patterns (see Wieling, 2012 for examples, albeit in a different field), which can subsequently be used to predict the outcome of a judgment. Such an approach would clearly be beneficial for the field of law. Surprisingly, a recent study (Vols & Jacobs, 2016) showed that between 2006 and 2016 fewer than 25 publications in Dutch legal journals were published involving statistics to analyse case law. While a quantitative approach to analysing case law is more prevalent in the US, it is primarily focused on specific American legal issues, and frequently contains serious methodological flaws (Epstein & King, 2002; Epstein & Martin, 2014).

    In computational linguistics, specific characteristics of legal texts have been studied (see Francesconi, Montemagni et al. (eds.), 2010), but hardly any studies have attempted to use linguistic characteristics to predict judicial decisions. A very recent exception (also illustrating the timeliness of the project idea) by Aletras et al. (2016) reported an accuracy of 79% in predicting the judgments of the European Court of Human Rights. However, they focused only on a small sample (600 judgments) and used simplistic linguistic features (such as word frequency). The goal of this PhD project is therefore to take a more comprehensive, linguistically-oriented approach incorporating all available data, thereby developing a system which is able to detect common patterns in legal big data and use these to predict the outcome of a judgment.

    This project is funded by the Young Academy Groningen.

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    Speech deterioration in Parkinson's disease

    (2017 - 2020)

    (PhD student: Jidde Jacobi, Co-supervisors: Roel Jonkers, Michael Proctor, and Ben Maassen)

    In this IDEALAB-funded project, we investigate speech articulation in Parkinson's disease. Parkinsons disease is a degenerative neurological disorder that is characterised by a decay of motor function. Due to a loss of dopaminergic cells in the substantia nigra, both motor control as well as initiation deteriorate over time, which frequently leads to difficulties in speech producation, a phenomenom that is known as hypokinetic dysarthria. Previous acoustics studies have shown that pitch height and variation, articulation of both vowels and consonants and voice quality are often affected in hypokinetic dysarthria. So far however, the role of kinematics in hypokinetic dysarthria has not been given much attention. Yet, thanks to the recent development of electromagnetic articulography (EMA) it is now possible to track and measure the kinematic movements of the lips, the tongue and the jaw during speech production. This means that a more fine-grained analysis of the articulation difficulties in hypokinetic dysarthria can be performed. In this future study, the velocity, amplitude and coordination of kinematic gestures will be under investigation. Specifically, the temporal overlap of speech gestures will be studied as well as the location and rate of contractions within the vocal tract. In total, 30 Parkinson’s patients with hypokinetic dysarthria will be included. Another 30 participants will serve as healthy controls. In doing so, a detailed view of coordination in hypokinetic dysarthria will be obtained which will lead to a better understanding of the speech disorder. Moreover, it will shed new light on leading theories that have only approached speech from an acoustic viewpoint. Ultimately, the knowledge that will be obtained within this study can improve a early diagnosis of Parkinson’s disease and also dramatically improve speech therapy. In addition, it will also provide more general insight into the kinematics of speech.

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    Using ultrasound to investigate and improve L2 pronunciation

    (2017 - 2019)

    (Research assistant: Lisanne de Jong)

    In this project we aim to investigate how visualizing tongue movements using ultrasound may be used to help a learner to improve his or her pronunciation in a second language (L2). This project is funded by the Groningen University Fund and De Jonge Akademie.

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    Identifying Dutch accents automatically

    (2017 - 2018)

    (Post-doc: Aki Kunikoshi, Data scientists: Herbert Kruitbosch and Arya Babai, Collaborator: David van Leeuwen)

    In this project we focused on automatically detecting Dutch accents on the basis of data from the Sprekend Nederland data. Particularly, we were interested in identifying the acoustic and segmental characteristics of the different accents. This project is funded by the Centre for Digital Humanities of the University of Groningen. Some results of the project can be found here.

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    Automatic recognition of Frisian speakers

    (2017 - 2018)

    (Co-PI: Nanna Hilton, Post-doc: Aki Kunikoshi, Data scientists: Herbert Kruitbosch)

    In this project, we have studied the effects of one language on another in our voices, by considering how recognizable Frisian phonological traits are in speakers' production of their first language, Frisian, as well as in their second language, Dutch. This project is funded by the University of Groningen (Data Science Projects 2017). A publication regarding this project is currently in preparation.

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    Speech recognition for congenitally blind speakers

    (2016 - 2017)

    (Researcher: Pauline Veenstra, Collaborator: Royal Dutch Visio)

    In this project we investigated if the speech of congenitally blind speakers differs from that of sighted speakers, both from an articulatory as well as an acoustic perspective. Specifically, we investigate if automatic speech recognition performance differs between the two groups. This project was funded by VIVIS. The results of the project were presented at several conferences (e.g., see here: page 88).

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    Improving speech learning models and English pronunciation with articulography

    (2013 - 2017)

    (Collaborators: Patti Adank, Mark Tiede, Andrea Weber, R. Harald Baayen and others)

    In this project we have investigated articulatory differences between Dutch and German speakers' pronunciation of English versus those of native English speakers. Furthermore, we are assessing how visual feedback of the speech articulators may help improve non-native speakers' pronunciation of English. This project was funded by NWO (Veni grant). Results of the project can be found in several publications.

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    Investigating language variation physically

    (2012 - 2013)

    (Collaborators: R. Harald Baayen and team members in Tübingen)

    In this project (conducted at the University of Tübingen) we have investigated Dutch dialect variation using articulography. This project was funded by NWO (Rubicon grant). Results of the project can be found in several publications.

Lab facilities

In Speech Lab Groningen, we have the following equipment available for research projects:

Team

Hedwig Sekeres

Research assistant and MA student

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Jidde Jacobi

PhD student

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Masha Medvedeva

PhD student

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Teja Rebernik

PhD student

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Martijn Bartelds

PhD student

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Wietse de Vries

PhD student

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Raoul Buurke

PhD student

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Interested in joining my lab?

I am always looking for excellent PhD candidates or research assistants. If you are interested in the field of dialect or language variation, speech production research, or computational linguistics, please contact me.

Publications

(h: 28)

Adapting monolingual models: data can be scarce when language similarity is high

de Vries*, W., Bartelds*, M., Nissim, M., & Wieling, M. (forthcoming, 2021)
Proceedings paper Findings of ACL. [* joint first authorship].

Abstract

For many (minority) languages, the resources needed to train large models are not available. We investigate the performance of zero-shot transfer learning with as little data as possible, and the influence of language similarity in this process. We retrain the lexical layers of four BERT-based models using data from two low-resource target language varieties, while the Transformer layers are independently fine-tuned on a POS-tagging task in the model's source language. By combining the new lexical layers and fine-tuned Transformer layers, we achieve high task performance for both target languages. With high language similarity, 10MB of data appears sufficient to achieve substantial monolingual transfer performance. Monolingual BERT-based models generally achieve higher downstream task performance after retraining the lexical layer than multilingual BERT, even when the target language is included in the multilingual model.

A review of data collection practices using electromagnetic articulography

Rebernik, T., Jacobi, J., Jonkers, R., Noiray, A., & Wieling, M. (2021)
Journal paper Key publication Laboratory Phonology.

Abstract

This paper reviews data collection practices in electromagnetic articulography (EMA) studies, with a focus on sensor placement. It consists of three parts: in the first part, we introduce electromagnetic articulography as a method. In the second part, we focus on existing data collection practices. Our overview is based on a literature review of 905 publications from a large variety of journals and conferences, identified through a systematic keyword search in Google Scholar. The review shows that experimental designs vary greatly, which in turn may limit researchers' ability to compare results across studies. In the third part of this paper we describe an EMA data collection procedure which includes an articulatory-driven strategy for determining where to position sensors on the tongue without causing discomfort to the participant. We also evaluate three approaches for preparing (NDI Wave) EMA sensors reported in the literature with respect to the duration the sensors remain attached to the tongue: 1) attaching out-of-the-box sensors, 2) attaching sensors coated in latex, and 3) attaching sensors coated in latex with an additional latex flap. Results indicate no clear general effect of sensor preparation type on adhesion duration. A subsequent exploratory analysis reveals that sensors with the additional flap tend to adhere for shorter times than the other two types, but that this pattern is inverted for the most posterior tongue sensor.

Prevalence of internalizing disorders, symptoms and traits across age using advanced non-linear methods

van Loo, H. M., Beijers, L., Wieling, M., de Jong, T. R., Schoevers, R. A., & Kendler, K. S. (2021)
Journal paper Psychological Medicine. doi:10.1017/S0033291721001148.

Abstract

Background: Most epidemiological studies show a decrease of internalizing disorders at older ages, but it is unclear how the prevalence exactly changes with age, and whether there are different patterns for internalizing symptoms and traits, and for men and women. This study investigates the impact of age and sex on the point prevalence across different mood and anxiety disorders, internalizing symptoms, and neuroticism.

Methods: We used cross-sectional data on 146,315 subjects, aged 18-80 years, from the Lifelines Cohort Study, a Dutch general population sample. Between 2012-2016, five current internalizing disorders - major depression, dysthymia, generalized anxiety disorder, social phobia and panic disorder - were assessed according to DSM-IV criteria. Depressive symptoms, anxiety symptoms, neuroticism, and negative affect were also measured. Generalized additive models were used to identify nonlinear patterns of internalizing disorders, symptoms and traits over lifetime, and to investigate sex differences.

Results: The point prevalence of internalizing disorders generally increased between the ages of 18-30 years, stabilized between 30-50, and decreased after age 50. The patterns of internalizing symptoms and traits were different. Negative affect and neuroticism gradually decreased after age 18. Women reported more internalizing disorders than men, but the relative difference remained stable across age (relative risk ~1.7).

Conclusions: The point prevalence of internalizing disorders was typically highest between age 30-50, but there were differences between the disorders, which could indicate differences in etiology. The relative gap between the sexes remained similar across age, suggesting that changes in sex hormones around the menopause do not significantly influence women's risk of internalizing disorders.

Accuracy assessment of two electromagnetic articulographs: NDI Wave and NDI Vox

Rebernik, T., Jacobi, J., Tiede, M., & Wieling, M. (forthcoming, 2021)
Journal paper JSLHR.

Abstract

Purpose: This study compares two electromagnetic articulographs (EMA) manufactured by Northern Digital, Inc.: the NDI Wave System (2008) and the NDI Vox-EMA System (2020).

Method: Four experiments were completed: (a) comparison of statically positioned sensors; 4(b) tracking dynamic movements of sensors manipulated using a motor-driven LEGO apparatus; (c) tracking small and large movements of sensors mounted in a rigid bar manipulated by hand; and (d) tracking movements of sensors rotated on a circular disc. We assessed spatial variability for statically positioned sensors, variability in the transduced Euclidean distances (EDs) between sensor pairs, and missing data rates. For sensors tracking circular movements, we compared the fit between fitted ideal circles and actual trajectories.

Results: The average sensor pair tracking error (i.e., the standard deviation of the EDs) was 1.37 mm for the WAVE and 0.12 mm for the VOX during automated trials at the fastest speed, and 0.35 mm for the WAVE and 0.14mm for the VOX during the tracking of large manual movements. The average standard deviation of the fitted circle radii charted by manual circular disc movements was 0.72mm for the WAVE sensors and 0.14mm for the VOX sensors. There was no significant difference between the WAVE and the VOX in the number of missing frames.

Conclusions: In general, the VOX system significantly outperformed the WAVE on measures of both static precision and dynamic accuracy (automated and manual). For both systems, positional precision and spatial variability were influenced by the sensors' position relative to the field generator unit (FGU; worse when further away).

Dialectology for computational linguists

Nerbonne, J., Heeringa, W., Prokić, J., & Wieling, M. (forthcoming, 2021)
Book chapter In: Marcos Zampieri, & Preslav Nakov (eds.) Similar Languages, Varieties, and Dialects: A Computational Perspective. Cambridge University Press.

L2 developmental measures from a dynamic perspective

Verspoor, M., Lowie, W., & Wieling, M. (forthcoming, 2021)
Book chapter In: Magali Paquot, & Bert LeBruyn (eds.) Learner Corpora Researchs Meets Second Language Acquisition. Cambridge University Press.

Regional Dialectology: Quantitative Approaches using R

Grieve, J., & Wieling, M. (in preparation, ~2021/2022)
Book Cambridge University Press. Book contract signed.

A novel paradigm to investigate phonetic convergence in interaction

Wieling, M., Tiede, M., Rebernik, T., de Jong, L., Braggaar, A., Bartelds, M., Medvedeva, M., Heisterkamp, P., Freire Offrede, T., Sekeres, H., Pot, A., van der Ploeg, M., Volkers, K., & Mills, G. (2020)
Proceedings paper 12th International Seminar on Speech Production.

Characterizing tongue tremor in Parkinson's disease using EMA

Jacobi, J., Rebernik, T., Jonkers, R., Maassen, B., Proctor, M., & Wieling, M. (2020)
Proceedings paper 12th International Seminar on Speech Production.

Experimental approaches in electromagnetic articulography

Rebernik, T., Jacobi, J., Jonkers, R., Noiray, A., & Wieling, M. (2020)
Proceedings paper 12th International Seminar on Speech Production.

Measuring foreign accent strength using an acoustic distance measure

Bartelds, M., de Vries, W., Richter, C., Liberman, M., & Wieling, M. (2020)
Proceedings paper 12th International Seminar on Speech Production.

Vowel production in congenitally blind and sighted Australian English speakers

Janić, M., Rebernik, T., Veenstra, P., Wissink, E., Wieling, M., & Proctor, M. (2020)
Proceedings paper 12th International Seminar on Speech Production.

Using ultrasound tongue imaging to improve L2 English pronunciation in Dutch students

de Jong, L., Rebernik, T., Vaziri, S., & Wieling, M. (2020)
Proceedings paper 12th International Seminar on Speech Production.

JURI SAYS: an automatic judgement prediction system for the European Court of Human Rights

Medvedeva, M., Xu, X., Wieling, M., & Vols, M. (2020)
Proceedings paper JURIX 2020.

Abstract

In this paper we present the web platform JURI SAYS that automatically predicts decisions of the European Court of Human Rights based on communicated cases, which are published by the court early in the proceedings and are often available many years before the final decision is made. Our system therefore predicts future judgements of the court. The platform is available at jurisays.com and shows the predictions compared to the actual decisions of the court. It is automatically updated every month by including the prediction for the new cases. Additionally, the system highlights the sentences and paragraphs that are most important for the prediction (i.e. violation vs. no violation of human rights).

LSDC - A comprehensive dataset for Low Saxon dialect classification

Siewert, J., Scherrer, Y., Wieling, M., & Tiedemann, J. (2020)
Proceedings paper VarDial 2020.

Abstract

We present a new comprehensive dataset for the unstandardised West-Germanic language Low Saxon covering the last two centuries, the majority of modern dialects and various genres, which will be made openly available in connection with the final version of this paper. Since so far no such comprehensive dataset of contemporary Low Saxon exists, this provides a great contribution to NLP research on this language. We also test the use of this dataset for dialect classification by training a few baseline models comparing statistical and neural approaches. The performance of these models shows that in spite of an imbalance in the amount of data per dialect, enough features can be learned for a relatively high classification accuracy.

The Impact of Alcohol on L1 vs. L2

Offrede, T., Jacobi, J., Rebernik, T., de Jong, L., Keulen, S., Veenstra, P., Noiray, A., & Wieling, M. (2020)
Journal paper Language and Speech.

Abstract

Alcohol intoxication is known to affect many aspects of human behavior and cognition; one of such affected systems is articulation during speech production. Although much research has revealed that alcohol negatively impacts pronunciation in a first language (L1), there is only initial evidence suggesting a potential beneficial effect of inebriation on articulation in a non-native language (L2). The aim of this study was thus to compare the effect of alcohol consumption on pronunciation in an L1 and an L2. Participants who had ingested different amounts of alcohol provided speech samples in their L1 (Dutch) and L2 (English), and native speakers of each language subsequently rated the pronunciation of these samples on their intelligibility (for the L1) and accent nativelikeness (for the L2). These data were analyzed with generalized additive mixed modeling. Participants' blood alcohol concentration indeed negatively affected pronunciation in L1, but it produced no significant effect on the L2 accent ratings. The expected negative impact of alcohol on L1 articulation can be explained by reduction in fine motor control. We present two hypotheses to account for the absence of any effects of intoxication on L2 pronunciation: (i) there may be a reduction in L1 interference on L2 speech due to decreased motor control or (ii) alcohol may produce a differential effect on each of the two linguistic subsystems.

A new acoustic-based pronunciation distance measure

Bartelds, M., Richter, C., Liberman, M., & Wieling, M. (2020)
Journal paper Frontiers in Artificial Intelligence.

Abstract

We present an acoustic distance measure for comparing pronunciations, and apply the measure to assess foreign accent strength in American-English by comparing speech of non-native American-English speakers to a collection of native American-English speakers. An acoustic-only measure is valuable as it does not require the time-consuming and error-prone process of phonetically transcribing speech samples which is necessary for current edit distance-based approaches. We minimize speaker variability in the data set by employing speaker-based cepstral mean and variance normalization, and compute word-based acoustic distances using the dynamic time warping algorithm. Our results indicate a strong correlation of r = -0.71 (p < 0.0001) between the acoustic distances and human judgments of native-likeness provided by more than 1,100 native American-English raters. Therefore, the convenient acoustic measure performs only slightly lower than the state-of-the-art transcription-based performance of r = -0.77. We also report the results of several small experiments which show that the acoustic measure is not only sensitive to segmental differences, but also to intonational differences and durational differences. However, it is not immune to unwanted differences caused by using a different recording device.

Using machine learning to predict decisions of the European Court of Human Rights

Medvedeva, M., Vols, M., & Wieling, M. (2020)
Journal paper Artificial Intelligence and Law, 28, 237-266.

Abstract

When courts started publishing judgements, big data analysis (i.e. largescale statistical analysis of case law and machine learning) within the legal domain became possible. By taking data from the European Court of Human Rights as an example, we investigate how Natural Language Processing tools can be used to analyse texts of the court proceedings in order to automatically predict (future) judicial decisions. With an average accuracy of 75% in predicting the violation of 9 articles of the European Convention on Human Rights our (relatively simple) approach highlights the potential of machine learning approaches in the legal domain. We show, however, that predicting decisions for future cases based on the cases from the past negatively impacts performance (average accuracy range from 58% to 68%). Furthermore, we demonstrate that we can achieve a relatively high classification performance (average accuracy of 65%) when predicting outcomes based only on the surnames of the judges that try the case.

Effectiveness of a dynamic usage based Computer Assisted Language program

Irshad, M., Keijzer, M., Wieling, M., & Verspoor, M. (2019)
Journal paper Dutch Journal of Applied Linguistics, 8(2), 137 - 162.

The influence of alcohol on L1 vs. L2 pronunciation

Wieling, M., Blankevoort, C., Hukker, V., Jacobi, J., de Jong, L., Keulen, S., Medvedeva, M., van der Ploeg, M., Pot, A., Rebernik, T., Veenstra, P., & Noiray, A. (2019)
Proceedings paper Proceedings of ICPhS 2019, pp. 3622-3626.

The effect of Levodopa on articulation in Parkinson's disease: A cross-linguistic study

Jacobi, J., Rebernik, T., Jonkers, R., Maassen, B., Proctor, M., & Wieling, M. (2019)
Proceedings paper Proceedings of ICPhS 2019, pp. 1069-1073.

Back from the future: nonlinear anticipation in adults and children's speech

Noiray, A., Wieling, M., Abakarova, D., Rubertus, E., & Tiede, M. (2019)
Journal paper Journal of Speech Language and Hearing Research, 62, 3033-3054.

Reproducibility in computational linguistics: are we willing to share?

Wieling, M., Rawee, J., & van Noord, G. (2018)
Journal paper Computational Linguistics, 44(4), 641 - 649.

Abstract

This study focuses on an essential precondition for reproducibility in computational linguistics: the willingness of authors to share relevant source code and data. Ten years after Ted Pedersen's influential ``Last Words'' contribution in Computational Linguistics, we investigate to what extent researchers in computational linguistics are willing and able to share their data and code. We surveyed all 395 full papers presented at the 2011 and 2016 ACL Annual Meetings, and identified if links to data and code were provided. If working links were not provided, authors were requested to provide this information. While data was often available, code was shared less often. When working links to code or data were not provided in the paper, authors provided the code in about one third of cases. For a selection of ten papers, we attempted to reproduce the results using the provided data and code. We were able to reproduce the results approximately for half of the papers. For only a single paper we obtained the exact same results. Our findings show that even though the situation appears to have improved comparing 2016 to 2011, empiricism in computational linguistics still largely remains a matter of faith (Pedersen, 2008). Nevertheless, we are somewhat optimistic about the future. Ensuring reproducibility is not only important for the field as a whole, but also for individual researchers: below we show that the median citation count for studies with working links to the source code are higher.

Post-editing effort of a novel with statistical and neural machine translation

Toral, A., Wieling, M., & Way, A. (2018)
Journal paper Frontiers in Digital Humanities, 5(doi: 10.3389/fdigh.2018.00009).

Abstract

We conduct the first experiment in the literature in which a novel is translated automatically and then post-edited by professional literary translators. Our case study is Warbreaker, a popular fantasy novel originally written in English, which we translate into Catalan. We translated one chapter of the novel (over 3,700 words, 330 sentences) with two data-driven approaches to Machine Translation (MT): phrase-based statistical MT (PBMT) and neural MT (NMT). Both systems are tailored to novels; they are trained on over 100 million words of fiction. In the post-editing experiment, six professional translators with previous experience in literary translation translate subsets of this chapter under three alternating conditions: from scratch (the norm in the novel translation industry), post-editing PBMT, and post-editing NMT. We record all the keystrokes, the time taken to translate each sentence, as well as the number of pauses and their duration. Based on these measurements, and using mixed-effects models, we study post-editing effort across its three commonly studied dimensions: temporal, technical and cognitive. We observe that both MT approaches result in increases in translation productivity: PBMT by 18%, and NMT by 36%. Post-editing also leads to reductions in the number of keystrokes: by 9% with PBMT, and by 23% with NMT. Finally, regarding cognitive effort, post-editing results in fewer (29% and 42% less with PBMT and NMT respectively) but longer pauses (14% and 25%).

Judicial decisions of the European Court of Human Rights: looking into the crystall ball

Medvedeva, M., Vols, M., & Wieling, M. (2018)
Proceedings paper Proceedings of the Conference on Empirical Legal Studies in Europe 2018.

Abstract

When courts started publishing judgements big data analysis (i.e. large-scale statistical analysis and machine learning) within the legal domain became possible. By taking data from the European Court of Human Rights as an example, we investigate how Natural Language Processing tools can be used to analyse texts of the court proceedings in order to automatically predict (future) judicial decisions. With an average accuracy of 75% in predicting the violation of 9 articles of the European Convention on Human Rights our (relatively simple) approach highlights the potential of machine learning approaches in the legal domain.

Analyzing dynamic phonetic data using generalized additive mixed modeling: a tutorial focusing on articulatory differences between L1 and L2 speakers of English

Wieling, M. (2018)
Journal paper Key publication Journal of Phonetics, 70, 86 - 116.

Abstract

In phonetics, many datasets are encountered which deal with dynamic data collected over time. Examples include diphthongal formant trajectories and articulator trajectories observed using electromagnetic articulography. Traditional approaches for analyzing this type of data generally aggregate data over a certain timespan, or only include measurements at a fixed time point (e.g., formant measurements at the midpoint of a vowel). In this paper, I discuss generalized additive modeling, a non-linear regression method which does not require aggregation or the pre-selection of a fixed time point. Instead, the method is able to identify general patterns over dynamically varying data, while simultaneously accounting for subject and item-related variability. An advantage of this approach is that patterns may be discovered which are hidden when data is aggregated or when a single time point is selected. A corresponding disadvantage is that these analyses are generally more time consuming and complex. This tutorial aims to overcome this disadvantage by providing a hands-on introduction to generalized additive modeling using articulatory trajectories from L1 and L2 speakers of English within the freely available R environment. All data and R code is made available to reproduce the analysis presented in this paper.

Individual differences in very young Chinese children's English vocabulary breadth and semantic depth: internal and external factors

Sun, H., Steinkrauss, R., Wieling, M., & de Bot, K. (2018)
Journal paper International Journal of Bilingual Education and Bilingualism, 21(4), 405 - 425.

Providers' competencies positively affect personal recovery of involuntarily admitted patients with severe mental illness: A prospective observational study

Jas, E., & Wieling, M. (2018)
Journal paper International Journal of Social Psychiatry, 64(2), 145 - 155.

Border effects among Catalan dialects

Wieling, M., Valls, E., Baayen, R. H., & Nerbonne, J. (2018)
Book chapter In: Dirk Speelman, Kris Heylen, & Dirk Geeraerts (eds.) Mixed Effects Regression Models in Linguistics. Berlin: Springer (Quantitative methods in the Humanities and Social Sciences), pp. 71 - 97.

Statistics for aggregate variationist analyses

Nerbonne, J., & Wieling, M. (2018)
Book chapter In: Charles Boberg, John Nerbonne, & Dominic Watt (eds.) Handbook of Dialectology. Boston: Wiley, pp. 400 - 414.

From Semantics to Dialectometry. Festschrift in Honor of John Nerbonne

Wieling, M., Kroon, M., van Noord, G., & Bouma, G. (eds.) (2017)
Book Tributes 32, College Publications. 418 pp.

itsadug: Interpreting Time Series and Autocorrelated Data Using GAMMs

van Rij, J., Wieling, M., Baayen, R. H., & van Rij, H. (2017)
R packageVersion 2.4

Identifying predictive features for textual genre classification: the key role of syntactic features

Cimino, A., Wieling, M., Dell'Orletta, F., Montemagni, S., & Venturi, G. (2017)
Proceedings paper Proceedings of the Fourth Italian Conference on Computational Linguistics, Paper 39.

Articulatory differences between L1 and L2 speakers of English

Wieling, M., Veenstra, P., Adank, P., & Tiede, M. (2017)
Proceedings paper Proceedings of the 11th International Seminar on Speech Production, Paper 1.

Individual alpha peak frequency predicts 10 Hz flicker effects on selective attention

Gulbinaite, R., van Viegen, T., Wieling, M., Cohen, M., & VanRullen, R. (2017)
Journal paper The Journal of Neuroscience, 37(42), 10173 - 10184.

Sharing is caring: the future of shared tasks

Nissim, M., Abzianidze, L., Evang, K., van der Goot, R., Haagsma, H., Plank, B., & Wieling, M. (2017)
Journal paper Computational Linguistics, 43(4), 897 - 904.

The power of character n-grams in native language identification

Kulmizev, A., Blankers, B., Bjerva, J., Nissim, M., van Noord, G., Plank, B., & Wieling, M. (2017)
Proceedings paper Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications, pp. 382 - 389.

Analysis of acoustic-to-articulatory speech inversion across different accents and languages

Sivaraman, G., Espy-Wilson, C., & Wieling, M. (2017)
Proceedings paper Proceedings of Interspeech 2017, pp. 974 - 978.

Quantitative identification of dialect-specific articulatory settings

Wieling, M., & Tiede, M. (2017)
Journal paper Journal of the Acoustical Society of America, 142(1), 389 - 394.

Eye-tracking the effect of word order in sentence comprehension in aphasia: Evidence from Basque, a free word order ergative language

Arantzeta, M., Bastiaanse, R., Burchert, F., Wieling, M., Zabaleta, M. M., & Laka, I. (2017)
Journal paper Language, Cognition and Neuroscience, 32(10), 1320 - 1343.

Multimodal character viewpoint in quoted dialogue sequences

Stec, K., Huiskes, M., Wieling, M., & Redeker, G. (2017)
Journal paper Glossa: a journal of general linguistics, 2(1), 39.

Exploring the role of extra-linguistic factors in defining dialectal variation patterns through cluster comparison.

Montemagni, S., & Wieling, M. (2017)
Book chapter In: Martijn Wieling, Martin Kroon, Gertjan van Noord, & Gosse Bouma (eds.) From Semantics to Dialectometry. Festschrift in honor of John Nerbonne. Tributes 32, London: College Publications, pp. 241 - 251. [Note: not peer-reviewed].

Variation and change in the use of hesitation markers in Germanic languages

Wieling, M., Grieve, J., Bouma, G., Fruehwald, J., Coleman, J., & Liberman, M. (2016)
Journal paper Key publication Language Dynamics and Change, 6(2), 199 - 234.

Abstract

In this study, we investigate crosslinguistic patterns in the alternation between UM, a hesitation marker consisting of a neutral vowel followed by a final labial nasal, and UH, a hesitation marker consisting of a neutral vowel in an open syllable. Based on a quantitative analysis of a range of spoken and written corpora, we identify clear and consistent patterns of change in the use of these forms in various Germanic languages (English, Dutch, German, Norwegian, Danish, Faroese) and dialects (American English, British English), with the use of UM increasing over time relative to the use of UH. We also find that this pattern of change is generally led by women and more educated speakers. Finally, we propose a series of possible explanations for this surprising change in hesitation marker usage that is currently taking place across Germanic languages.

Investigating dialectal differences using articulography

Wieling, M., Tomaschek, F., Arnold, D., Tiede, M., Bröker, F., Thiele, S., Wood, S. N., & Baayen, R. H. (2016)
Journal paper Key publication Journal of Phonetics, 59, 122 - 143.

Abstract

The present study uses electromagnetic articulography, by which the position of tongue and lips during speech is measured, for the study of dialect variation. By using generalized additive modeling to analyze the articulatory trajectories, we are able to reliably detect aggregate group differences, while simultaneously taking into account the individual variation of dozens of speakers. Our results show that two Dutch dialects show clear differences in their articulatory settings, with generally a more anterior tongue position in the dialect from Ubbergen in the southern half of the Netherlands than in the dialect of Ter Apel in the northern half of the Netherlands. A comparison with formant-based acoustic measurements further reveals that articulography is able to reveal interesting structural articulatory differences between dialects which are not visible when only focusing on the acoustic signal.

Read my points: effect of animation type when speech-reading from EMA data

James, K., & Wieling, M. (2016)
Proceedings paper Proceedings of the 14th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology, pp. 87 - 92.

ALT Explored: integrating an online dialectometric tool and an online dialect atlas

Wieling, M., Sassolini, E., Cucurullo, N., & Montemagni, S. (2016)
Proceedings paper Proceedings of LREC 2016, pp. 3265 - 3272.

How to analyze linguistic change using mixed models, growth curve analysis and generalized additive modeling

Winter, B., & Wieling, M. (2016)
Journal paper Journal of Language Evolution, 1(1), 7 - 18.

Infrequent forms: noise or not?

Wieling, M., & Montemagni, S. (2016)
Book chapter In: Marie-Hélène Côté, Remco Knooihuizen, & John Nerbonne (eds.) The Future of Dialects. Berlin: Language Science Press (Language Variation), pp. 215 - 224.

Tracking linguistic features underlying lexical variation patterns: a case study on Tuscan dialects

Wieling, M., & Montemagni, S. (2016)
Book chapter In: Marie-Hélène Côté, Remco Knooihuizen, & John Nerbonne (eds.) The Future of Dialects. Berlin: Language Science Press (Language Variation), pp. 117 - 134.

Automatically identifying characteristic features of non-native English accents

Bloem, J., Wieling, M., & Nerbonne, J. (2016)
Book chapter In: Marie-Hélène Côté, Remco Knooihuizen, & John Nerbonne (eds.) The Future of Dialects. Berlin: Language Science Press (Language Variation), pp. 155 - 172.

Age effects in L2 grammar processing as revealed by ERPs and how (not) to study them

Meulman, N., Wieling, M., Sprenger, S., Stowe, L., & Schmid, M. (2015)
Journal paper Key publication PLOS ONE, 10(12), e0143328.

Abstract

In this study we investigate the effect of age of acquisition (AoA) on grammatical processing in second language learners as measured by event-related brain potentials (ERPs). We compare a traditional analysis involving the calculation of averages across a certain time window of the ERP waveform, analyzed with categorical groups (early vs. late), with a generalized additive modeling analysis, which allows us to take into account the full range of variability in both AoA and time. Sixty-six Slavic advanced learners of German listened to German sentences with correct and incorrect use of non-finite verbs and grammatical gender agreement. We show that the ERP signal depends on the AoA of the learner, as well as on the regularity of the structure under investigation. For gender agreement, a gradual change in processing strategies can be shown that varies by AoA, with younger learners showing a P600 and older learners showing a posterior negativity. For verb agreement, all learners show a P600 effect, irrespective of AoA. Based on their behavioral responses in an offline grammaticality judgment task, we argue that the late learners resort to computationally less efficient processing strategies when confronted with (lexically determined) syntactic constructions different from the L1. In addition, this study highlights the insights the explicit focus on the time course of the ERP signal in our analysis framework can offer compared to the traditional analysis.

The role of frequency in the retrieval of nouns and verbs in aphasia

Bastiaanse, R., Wieling, M., & Wolthuis, N. (2015)
Journal paper Aphasiology, 30(11), 1221 - 1239.

Determinants of English accents

Wieling, M., Bloem, J., Baayen, R. H., & Nerbonne, J. (2015)
Proceedings paper Proceedings of the 6th Conference on Quantitative Investigations in Theoretical Linguistics, doi: 10.15496/publikation-8628.

Comparing L1 and L2 speakers using articulography

Wieling, M., Veenstra, P., Adank, P., Weber, A., & Tiede, M. (2015)
Proceedings paper Proceedings of ICPhS 2015, Paper 551.

Investigating dialectal differences using articulography

Wieling, M., Tomaschek, F., Arnold, D., Tiede, M., & Baayen, R. H. (2015)
Proceedings paper Proceedings of ICPhS 2015, Paper 231.

Advances in dialectometry

Wieling, M., & Nerbonne, J. (2015)
Journal paper Key publication Annual Review of Linguistics, 1, 243-264.

Abstract

Dialectometry applies computational and statistical analyses within dialectology, making work more easily replicable and understandable. This survey article first reviews the field briefly in order to focus on developments in the past five years. Dialectometry no longer focuses exclusively on aggregate analyses, but rather deploys various techniques to identify representative and distinctive features with respect to areal classifications. Analyses proceeding explicitly from geostatistical techniques have just begun. The exclusive focus on geography as explanation for variation has given way to analyses combining geographical, linguistic, and social factors underlying language variation. Dialectometry has likewise ventured into diachronic studies and has also contributed theoretically to comparative dialectology and the study of dialect diffusion. Although the bulk of research involves lexis and phonology, morphosyntax is receiving increasing attention. Finally, new data sources and new (online) analytical software are expanding dialectometry's remit and its accessibility.

The differential effects of direct and indirect speech on discourse comprehension in Dutch and English listeners with and without aphasia

Groenewold, R., Bastiaanse, R., Nickels, L., Wieling, M., & Huiskes, M. (2015)
Journal paper Aphasiology, 29(6), 685 - 704.

Social, geographical, and lexical influence on Dutch dialect pronunciations

Ko, V., Wieling, M., Wit, E., Nerbonne, J., & Krijnen, W. (2014)
Journal paper Computational Linguistics in the Netherlands Journal, 4(2), 253 - 269.

Lexical differences between Tuscan dialects and standard Italian: accounting for geographic and socio-demographic variation using generalized additive mixed modeling

Wieling, M., Montemagni, S., Nerbonne, J., & Baayen, R. H. (2014)
Journal paper Key publication Language, 90(3), 669 - 692.

Abstract

This study uses a generalized additive mixed-effects regression model to predict lexical differences in Tuscan dialects with respect to standard Italian. We used lexical information for 170 concepts used by 2,060 speakers in 213 locations in Tuscany. In our model, geographical position was found to be an important predictor, with locations more distant from Florence having lexical forms more likely to differ from standard Italian. In addition, the geographical pattern varied significantly for low- versus high-frequency concepts and older versus younger speakers. Younger speakers generally used variants more likely to match the standard language. Several other factors emerged as significant. Male speakers as well as farmers were more likely to use lexical forms different from standard Italian. In contrast, higher-educated speakers used lexical forms more likely to match the standard. The model also indicates that lexical variants used in smaller communities are more likely to differ from standard Italian. The impact of community size, however, varied from concept to concept. For a majority of concepts, lexical variants used in smaller communities are more likely to differ from the standard Italian form. For a minority of concepts, however, lexical variants used in larger communities are more likely to differ from standard Italian. Similarly, the effect of the other community- and speaker-related predictors varied per concept. These results clearly show that the model succeeds in teasing apart different forces influencing the dialect landscape and helps us to shed light on the complex interaction between the standard Italian language and the Tuscan dialectal varieties. In addition, this study illustrates the potential of generalized additive mixed-effects regression modeling applied to dialect data.

Measuring foreign accent strength in English: validating Levenshtein distance as a measure

Wieling, M., Bloem, J., Mignella, K., Timmermeister, M., & Nerbonne, J. (2014)
Journal paper Language Dynamics and Change, 4(2), 253 - 269.

Assessing the readability of sentences: which corpora and features?

Dell'Orletta, F., Wieling, M., Cimino, A., Venturi, G., & Montemagni, S. (2014)
Proceedings paper Proceedings of the 9th Workshop on Innovative Use of NLP for Building Educational Applications, pp. 163 - 173.

Vowel articulation affected by word frequency

Tomaschek, F., Tucker, B. V., Wieling, M., & Baayen, R. H. (2014)
Proceedings paper Proceedings of the 10th International Seminar on Speech Production, pp. 429 - 432.

The effects of direct and indirect speech on discourse comprehension in Dutch listeners with and without aphasia

Groenewold, R., Bastiaanse, R., Nickels, L., Wieling, M., & Huiskes, M. (2014)
Journal paper Aphasiology, 28(7), 862 - 884.

A cognitively grounded measure of pronunciation distance

Wieling, M., Nerbonne, J., Bloem, J., Gooskens, C., Heeringa, W., & Baayen, R. H. (2014)
Journal paper PLOS ONE, 9(1), e75734.

Analyzing the BBC Voices data: contemporary English dialect areas and their characteristic lexical variants

Wieling, M., Upton, C., & Thompson, A. (2014)
Journal paper Literary and Linguistic Computing, 29(1), 107 - 117.

Word frequency, vowel length and vowel quality in speech production: an EMA study of the importance of experience

Tomaschek, F., Wieling, M., Arnold, D., & Baayen, R. H. (2013)
Proceedings paper Proceedings of Interspeech 2013, pp. 1302 - 1306.

Measuring socially motivated pronunciation differences

Nerbonne, J., van Ommen, S., Gooskens, C., & Wieling, M. (2013)
Book chapter In: Lars Borin, & Anju Saxena (eds.) Approaches to Measuring Linguistic Differences. Berlin: Mouton De Gruyter, pp. 107 - 140.

Physical predictors of cognitive performance in healthy older adults: a cross-sectional analysis

Blankevoort, G., Scherder, E., Wieling, M., Hortobágyi, T., Brouwer, W., Geuze, R., & van Heuvelen, M. (2013)
Journal paper PLOS ONE, 8(7), e70799.

Voices dialectometry at the University of Groningen

Wieling, M. (2013)
Book chapter In: Clive Upton, & Bethan Davies (eds.) Analysing 21st-century British English: Conceptual and Methodological Aspects of the BBC 'Voices' Project. London: Routledge, pp. 208 - 218.

Analyzing phonetic variation in the traditional English dialects: simultaneously clustering dialects and phonetic features

Wieling, M., Shackleton Jr., R. G., & Nerbonne, J. (2013)
Journal paper Literary and Linguistic Computing, 28(1), 31 - 41.

Synchronic patterns of Tuscan phonetic variation and diachronic change: evidence from a dialectometric study

Montemagni, S., Wieling, M., de Jonge, B., & Nerbonne, J. (2013)
Journal paper Literary and Linguistic Computing, 28(1), 157 - 172.

Linguistic advergence and divergence in north-western Catalan: a dialectometric investigation of dialect leveling and border effects

Valls, E., Wieling, M., & Nerbonne, J. (2013)
Journal paper Literary and Linguistic Computing, 28(1), 119 - 146.

Neuter is not common in Dutch: eye movements reveal asymmetrical gender processing

Loerts, H., Wieling, M., & Schmid, M. (2013)
Journal paper Journal of Psycholinguistic Research, 42(6), 551 - 570.

Applying the Levenshtein distance to Catalan dialects: a brief comparison of two dialectometric approaches

Valls, E., Nerbonne, J., Prokić, J., Wieling, M., Clua, E., & Lloret, M. (2012)
Journal paper Verba. Anuario Galego de Filoloxía, 39, 35 - 61.

A Quantitative Approach to Social and Geographical Dialect Variation

Wieling, M. (2012)
DissertationUniversity of Groningen. 178 pp.

Inducing a measure of phonetic similarity from pronunciation variation

Wieling, M., Margaretha, E., & Nerbonne, J. (2012)
Journal paper Journal of Phonetics, 40(2), 307 - 314.

Patterns of language variation and underlying linguistic features: a new dialectometric approach

Montemagni, S., Wieling, M., de Jonge, B., & Nerbonne, J. (2012)
Book chapter In: Patricia Bianchi, Nicola De Blasi, Chiara De Caprio, & Francesco Montuori (eds.) La Variazione Nell'italiano e Nella Sua Storia. Varietà e Varianti Linguistiche e Testuali. Atti dell'XI Congresso SILFI. Firenze: Franco Cesati Editore (Società Internazionale di Linguistica e Filologia Italiana), pp. 879 - 89. [Note: not peer-reviewed].

Inducing phonetic distances from dialect variation

Wieling, M., Margaretha, E., & Nerbonne, J. (2011)
Journal paper Computational Linguistics in the Netherlands Journal, 1, 109 - 118.

Quantitative social dialectology: explaining linguistic variation geographically and socially

Wieling, M., Nerbonne, J., & Baayen, R. H. (2011)
Journal paper PLOS ONE, 6(9), e23613.

Measuring linguistic variation commensurably

Wieling, M., & Nerbonne, J. (2011)
Journal paper Dialectologia, Special Issue II: Production & Perception and Attitude, 141 - 162.

Bipartite spectral graph partitioning for clustering dialect varieties and detecting their linguistic features

Wieling, M., & Nerbonne, J. (2011)
Journal paper Computer Speech and Language, 25(3), 700 - 715.

Some further dialectometrical steps

Nerbonne, J., Prokić, J., Wieling, M., & Gooskens, C. (2010)
Book chapter In: Gotzon Aurrekoexea, & José Luis Ormaetxea (eds.) Tools for Linguistic Variation. Bilbao: Supplements of the Anuario de Filologia Vasca "Julio de Urquijo", pp. 41 - 56.

Hierarchical spectral partitioning of bipartite graphs to cluster dialects and identify distinguishing features

Wieling, M., & Nerbonne, J. (2010)
Proceedings paper Proceedings of the 2010 Workshop on Graph-based Methods for Natural Language Processing, pp. 33 - 41.

The impact of online video lecture recordings and automated feedback on student performance

Wieling, M., & Hofman, A. (2010)
Journal paper Computers and Education, 54(4), 992 - 998.

The face reveals athletic flair: better National Football League quarterbacks are better looking

Williams, K., Park, J., & Wieling, M. (2010)
Journal paper Personality and Individual Differences, 48, 112 - 116.

A quantitative examination of variation in Dutch Low Saxon morphology

Heeringa, W., Wieling, M., van den Berg, B., & Nerbonne, J. (2009)
Book chapter In: Alexandra Lenz, Charlotte Gooskens, & Siemon Reker (eds.) Low Saxon Dialects across Borders - Niedersächsische Dialekte über Grenzen hinweg. Stuttgart: Franz Steiner Verlag (ZDL-Beiheft 138), pp. 195 - 216.

Bipartite spectral graph partitioning to co-cluster varieties and sound correspondences in dialectology

Wieling, M., & Nerbonne, J. (2009)
Proceedings paper Proceedings of the 2009 Workshop on Graph-based Methods for Natural Language Processing, pp. 14 - 22.

Evaluating the pairwise string alignment of pronunciations

Wieling, M., Prokić, J., & Nerbonne, J. (2009)
Proceedings paper Proceedings of the EACL 2009 Workshop on Language Technology and Resources for Cultural Heritage, Social Sciences, Humanities, and Education, pp. 26 - 34.

Multiple sequence alignments in linguistics

Prokić, J., Wieling, M., & Nerbonne, J. (2009)
Proceedings paper Proceedings of the EACL 2009 Workshop on Language Technology and Resources for Cultural Heritage, Social Sciences, Humanities, and Education, pp. 18 - 25.

Sex-specific relationship between digit ratio (2D:4D) and romantic jealousy

Park, J., Wieling, M., Buunk, B., & Massar, K. (2008)
Journal paper Personality and Individual Differences, 44, 1039 - 1045.

Dialect pronunciation comparison and spoken word recognition

Wieling, M., & Nerbonne, J. (2007)
Proceedings paper Proceedings of the RANLP 2007 Workshop on Computational Phonology, pp. 71 - 78.

Inducing Sound Segment Differences using Pair Hidden Markov Models

Wieling, M., Leinonen, T., & Nerbonne, J. (2007)
Proceedings paper Proceedings of Ninth Meeting of the ACL Special Interest Group in Computational Morphology and Phonology, pp. 48 - 56.

An aggregate analysis of pronunciation in the Goeman-Taeldeman-van Reenen-Project data

Wieling, M., Heeringa, W., & Nerbonne, J. (2007)
Journal paper Taal en Tongval, 59, 84 - 116.

Does the face reveal athletic flair? Positions in team sports and facial attractiveness

Park, J., Buunk, B., & Wieling, M. (2007)
Journal paper Personality and Individual Differences, 43, 1960 - 1965.

Comparison of Dutch Dialects

Wieling, M. (2007)
Master thesisUniversity of Groningen. 87 pp.

Parsing partially bracketed input

Wieling, M., Nederhof, M., & van Noord, G. (2006)
Proceedings paper Proceedings of the Sixteenth Computational Linguistics in the Netherlands, pp. 1 - 16.

Presentations

Statistics workshop for linguists

I frequently teach (invited) statistics courses for linguists focusing on generalized additive modeling.This technique, which is also able to take into account subject- and item-related variability (i.e. similar to mixed-effects regression) is important as it allows to model complex non-linear relationships between predictors and the dependent variable (e.g., time-series data such as EEG data). I've been invited to teach these courses at (e.g.,) Cambridge, Montréal and Toulouse. Slides (which are regularly updated) of these courses can be found here. If you are interested in this type of statistics course (generally ranging from two to five days), you are welcome to contact me. Note that I do ask a fee for teaching these courses.

Upcoming presentations

  • No upcoming presentations scheduled at present

Past invited presentations

  1. Approaches to investigating language variation and supporting minority languages (invited presentation). University of Helsinki, (online), April 15 - May 11, 2021.
  2. GAM consultation (invited course). Walter Reed National Military Medical Center (Stephanie Kuchinsky), (online), March 21 - June 2, 2021.
  3. GAM Workshop (invited course). Universität Zürich, online, December 7, 2020.
  4. Generalized additive modeling (invited course). University of Salzburg, Salzburg, Austria, November 21 - 22, 2019.
  5. The beauty of dialect variation (invited presentation). Festival della Scienza, Genua, Italy, October 27, 2019.
  6. Investigating pronunciation variation from an aggregate perspective: from dialectometry to articulography (keynote) (invited presentation). Conference on Experimental Approaches to Perception and Production of Language Variation (ExAPP), Münster, Germany, September 26 - 28, 2019.
  7. Dialectometry: modeling the influence of geography in dialect variation (invited presentation). University of Oldenburg, Oldenburg, Germany, July 4, 2019.
  8. Dialectometry (invited course). University of Malta, Malta, June 27 - 28, 2019.
  9. Generalized aditive modeling to analyze time series (invited presentation). Vrije Universiteit Brussel, Brussel, Belgium, October 2, 2018.
  10. Dialectometry (invited course). Linguistic Convergence Laboratory, Higher School of Economics, Moscow, Russia, September 10 - 14, 2018.
  11. Generalized additive modeling for phonetics (invited course). Humboldt-Universität zu Berlin, Institut für deutsche Sprache und Linguistik, Berlin, Germany, August 30 - 31, 2018.
  12. (Mixed-effects) regression and generalized additive modeling (invited course). Universität Stuttgart, Stuttgart, Germany, May 3 - 4, 2018.
  13. Statistics for Linguistics (invited course). LOT Winter School, Amsterdam, January 8 - 12, 2018.
  14. Generalized additive modeling (invited presentation). Institut für Phonetik und Sprachverarbeitung, Ludwig-Maximilians-Universität München, Munich, Germany, December 20, 2017.
  15. Generalized additive modeling (invited presentation). Winter School on Multilingualism, Groningen, November 9 - 10, 2017.
  16. Quantitative analyses of dialect variation (invited presentation). Meertens Instituut, Amsterdam, October 24, 2017.
  17. Discovering articulatory patterns using generalized additive modeling (invited presentation). Dynamic Modeling III workshop, Cologne, Germany, July 18 - 19, 2017.
  18. Generalized additive modeling as a useful tool for dialectometry (invited presentation). Sociolectometry Panel, ICLaVE, Málaga, Spain, June 6 - 9, 2017.
  19. Statistics for linguists in R (invited course). Istituto di Linguistica Computazionale, Consiglio Nazionale delle Ricerche, Pisa, Italy, May 2 - 5, 2017.
  20. Mixed-effects regression and generalized additive modeling (invited course). Centre de Recherche Cerveau & Cognition, Toulouse, France, March 30 - 31, 2017.
  21. Using generalized additive modeling for analyzing articulography data (and other time series data) (invited presentation). 5th International Winterschool "Speech Perception and Production", Chorin, Germany, January 9 - 13, 2017.
  22. Modeling the influence of geography in dialect variation (invited presentation). FLAMES-colloquium "Topics for Spatial Statistics", Leuven, Belgium, November 28, 2016.
  23. Investigating language variation quantitatively (invited presentation). EuroScience Open Forum 2016, Manchester, United Kingdom, July 23 - 27, 2016.
  24. Pronunciation variation on the tip of the tongue (invited presentation). BCN Winter meeting, Groningen, February 11, 2016.
  25. Investigating language variation using articulography (invited presentation). Netherlands Cancer Institute, Amsterdam, October 13, 2015.
  26. Generalized additive modeling (invited course). McGill, Neurocognition of Language Lab, Montréal, Canada, March 20 - 22, 2015.
  27. Mixed-effects regression and generalized additive modeling for linguists (invited course). Universität Tübingen, Englisches Seminar, Tübingen, Germany, February 9 - 10, 2015.
  28. Mixed-effects regression and generalized additive modeling for linguists (invited course). Universität Oldenburg, Institut für Niederlandistik, Oldenburg, Germany, February 2 - 3, 2015.
  29. Mixed-effects regression and generalized additive modeling for linguists (invited course). University of Cambridge, Department of Theoretical and Applied Linguistics, Cambridge, United Kingdom, January 13 - 14, 2015.
  30. Methods in Dialectometry (invited presentation). Ghent University, Department of Linguistics, Ghent, Belgum, October 16, 2014.
  31. Comparing pronunciations on the basis of transcriptions and articulography (invited presentation). Radboud University, Centre for Language Studies, Nijmegen, October 15, 2014.
  32. What the tongue can tell us about dialects? (invited presentation). Frontiers of Language Variation Workshop, Methods in Dialectology XV, Groningen, August 11 - 14, 2014.
  33. Generalized additive modeling for linguists (invited course). University Leiden, Center of Linguistics, Leiden, July 10 - 11, 2014.
  34. Mixed-effects regression and generalized additive modeling for linguists (invited course). Universität Oldenburg, Institut für Niederlandistik, Oldenburg, Germany, June 30 - July 1, 2014.
  35. Introduction to mixed-effects regression for (psycho)linguists (invited presentation). IMS Stuttgart, Stuttgart, Germany, December 16, 2013.
  36. Integrating traditional dialectology and sociolinguistics: generalized additive modeling (invited presentation). New Ways of Analyzing Variation (NWAV) 42, Pittsburgh, USA, October 17 - 20, 2013 [with R. Harald Baayen].
  37. Inducing and using phonetic similarity (invited presentation). Language Diversity Conference, Groningen, July 20, 2013 [with John Nerbonne].
  38. A sociolinguistic analysis of linguistically sensitive dialectal word pronunciation distances (invited presentation). Workshop on Computational Approaches to the Study of Dialectal and Typological Variation, ESSLLI 2012, Opole, Poland, August 6 - 10, 2012.
  39. Mixed-effects regression analyses of eyetracking data (invited presentation). Eye-tracking and EEG workshop, Groningen, July 7, 2011.
 
 
 
 

Past presentations

  1. A novel paradigm to investigate phonetic convergence in interaction (poster presentation). 12th International Seminar on Speech Production, online, December 18, 2020.
  2. The influence of alcohol on L1 vs. L2 pronunciation (poster presentation). 19th International Congress of Phonetic Sciences, Melbourne, Australia, August 5 - 9, 2019.
  3. The beauty of language variation (presentation). AGM Global Young Academy, Halle, Germany, May 2, 2019.
  4. Generalized additive modeling (guest lecture). University of Auckland, Auckland, New Zealand, December 12, 2018.
  5. Tutorial on generalized additive modelling to analyze time-series data (course). 17th Speech Science and Technology Conference, Coogee, Australia, December 4, 2018.
  6. Generalized additive modeling (guest lecture). Centre for Language Sciences, Macquarie University, Sydney, Australia, December 3, 2018.
  7. Generalized additive modeling to analyze articulatory data (guest lecture). Department of Information and Communication Engineering, University of Tokyo, Tokyo, Japan, November 5, 2018.
  8. Introductory course on Advanced Regression Methods for Linguistics (course). ESSLLI 2018, Sofia, Bulgaria, August 6 - 10, 2018.
  9. Articulatory differences between L1 and L2 speakers of English (presentation). Conference on Multilingualism, Groningen, November 6 - 9, 2017.
  10. Articulatory differences between L1 and L2 speakers of English (presentation). 11th International Seminar on Speech Production, Tianjin, China, October 16 - 19, 2017.
  11. Dialect-specific articulatory settings (presentation). Methods in Dialectology XVI, Tokyo, Japan, August 7 - 11, 2017.
  12. Articulatory differences between L1 and L2 speakers of English (poster presentation). 7th International Conference on Speech Motor Control, Groningen, July 5 - 8, 2017.
  13. Determinants of English Accents (presentation). 6th Conference on Quantitative Investigations in Theoretical Linguistics, Tübingen, Germany, November 4 - 6, 2015.
  14. Taalvariatie: patronen in uitspraak en tongbewegingen (guest lecture). De Jonge Akademie meeting, Groningen, September 21, 2015.
  15. Investigating dialectal differences using articulography (poster presentation). 18th International Congress of Phonetic Sciences, Glasgow, United Kingdom, August 10 - 14, 2015.
  16. Analyzing time series data using generalized additive modeling (course). LSA Institute, Chicago, USA, July 6 - 17, 2015 [with Jacolien van Rij].
  17. Measuring foreign accent strength (guest lecture). University of Cambridge, Department of Theoretical and Applied Linguistics, Cambridge, United Kingdom, January 13, 2015.
  18. Patterns of language variation (guest lecture). Digital Humanities Day 2014, Groningen, October 31, 2014.
  19. Gabmap tutorial (guest lecture). Ghent University, Department of Linguistics, Ghent, Belgium, October 15, 2014.
  20. Comparing dialect and accented pronunciations on the basis of transcriptions and articulography (guest lecture). McGill, Center of Research on Brain, Language and Music, Montréal, Canada, September 18, 2014.
  21. Analyzing linguistic time-series data with generalized additive modeling in R: a case study using ERP data (guest lecture). McGill, Motor Control Laboratory, Montréal, Canada, September 17, 2014.
  22. Comparing dialect and accented pronunciations on the basis of transcriptions and articulography (guest lecture). Linguistic Data Consortium, Philadelphia, USA, September 12, 2014.
  23. Generalized additive models in R (guest lecture). Haskins Laboratories, New Haven, USA, September 9, 2014.
  24. Validating and using the PMI-based Levenshtein distance as a measure of foreign accent strength (poster presentation). Methods in Dialectology XV, Groningen, August 11 - 15, 2014 [best poster award].
  25. Accessing large dialect databases on RADAR (presentation). Methods in Dialectology XV, Groningen, August 11 - 14, 2014 [with Clive Upton].
  26. Large-scale analysis of articulatory trajectories using generalized additive modeling (poster presentation). 10th International Seminar on Speech Production, Cologne, Germany, May 5 - 8, 2014.
  27. Comparing pronunciations on the basis of transcriptions and articulography (guest lecture). University College London, Department of Speech Hearing and Phonetic Sciences, London, United Kingdom, April 8, 2014.
  28. Articulography for studying language variation (guest lecture). Haskins Laboratories, New Haven, USA, October 24, 2013.
  29. Articulography for studying language variation (guest lecture). City University New York, Speech Production, Acoustics and Perception Laboratory, New York, USA, October 16, 2013.
  30. A cognitively grounded measure of pronunciation distance (presentation). Donders Workshop, Radboud University, Nijmegen, September 23, 2013 - May 11, 2021.
  31. A cognitively grounded automatic measure of pronunciation distance (presentation). 5th Conference on Quantitative Investigations in Theoretical Linguistics, Leuven, Belgium, September 12 - 14, 2013.
  32. Hierarchical spectral partitioning of bipartite graphs to cluster dialects and identify distinguishing features (guest lecture). Istituto di Linguistica Computazionale, Consiglio Nazionale delle Ricerche, Pisa, Italy, July 17, 2013.
  33. Comparing pronunciation on the basis of transcriptions and articulography (guest lecture). Università di Pisa, Dipartimento di Filologia, Letteratura e Linguistica, Pisa, Italy, July 16, 2013.
  34. Mixed-effects regression and generalized additive modeling in linguistics (course). LOT Summer School, Groningen, June 24 - 28, 2013 [with Jacolien van Rij].
  35. Co-clustering varieties and linguistic features using bipartite spectral graph partitioning (poster presentation). Forum Sprachvariation, Erlangen, Germany, October 14 - 15, 2012.
  36. Lexical differences between Tuscan dialects and standard Italian: a sociolinguistic analysis using generalized additive mixed modeling (presentation). Leuven Statistics Days, Leuven, Belgium, June 7 - 8, 2012.
  37. A quantitative investigation of English accents (poster presentation). BCN New Year's Meeting, Groningen, February 2, 2012 [best poster award].
  38. Segment distances and foreign accents (guest lecture). LOT Winter School, Tilburg, January 12, 2012.
  39. Gabmap tutorial (guest lecture). Göteborgs Universitet, Gothenburg, Sweden, October 26, 2011 [with John Nerbonne and Therese Leinonen].
  40. Inducing a measure of phonetic similarity from dialect variation (presentation). Workshop on Comparing Approaches to Measuring Linguistic Differences, Gothenburg, Sweden, October 24 - 25, 2011.
  41. A sociolinguistic analysis of aggregate dialect distances (presentation). Methods in Dialectology XIV, London (ON), Canada, August 1 - 5, 2011.
  42. A sociolinguistic analysis of dialect distances (poster presentation). BCN New Year's Meeting, Groningen, February 17, 2011.
  43. On the sublinear distribution of linguistic variation with respect to geography (presentation). Forum Sprachvariation, Erlangen, Germany, October 14 - 15, 2010.
  44. Dialectometry and hierarchical bipartite spectral graph partitioning (guest lecture). Makerere University, Department of Machine Learning, Kampala, Uganda, September 23, 2010.
  45. Text Manipulation and Hidden Markov Models (course). Makerere University, College of Computing and Information Sciences, Kampala, Uganda, September 20 - 22, 2010.
  46. Modelling geography's influence on language variation: calibrating linguistic measurements (presentation). Cultural Evolution in Spatially Structured Populations Conference, London, United Kingdom, September 13 - 15, 2010.
  47. Dialectometry in Groningen (guest lecture). University of Alberta, Department of Linguistics, Edmonton, Canada, August 11, 2010.
  48. Hierarchical bipartite spectral graph partitioning to cluster dialect varieties and determine their most important linguistic features (presentation). TextGraphs-5 ACL Workshop, Uppsala, Sweden, July 16, 2010.
  49. A graph-theoretic analysis of English dialects (presentation). Bloomsday 2010: Echoes of Albion Workshop, Groningen, June 16, 2010.
  50. On the sublinear distribution of linguistic variation with respect to geography (presentation). 31st TABU Dag, Groningen, June 3 - 4, 2010.
  51. Co-clustering varieties and linguistic features using bipartite spectral graph partitioning (presentation). Computational Linguistics in The Netherlands 20, Utrecht, February 5, 2010 - May 11, 2021.
  52. Understanding Séguy's law: on the sublinear distribution of linguistic variation with respect to geography (presentation). Past and Present Processes of Dialect Convergence: Data and Methods, Amsterdam, February 4, 2010 [with John Nerbonne].
  53. Bipartite spectral graph partitioning to co-cluster varieties and sound correspondences in dialectology (presentation). TextGraphs-4 ACL Workshop, Singapore, August 7, 2009.
  54. Tools for detecting geographical and structural affinities (presentation). Workshop on Small Tools for Cross-Linguistic Research, Utrecht, June 15 - 16, 2009.
  55. Evaluating the pairwise string alignment of pronunciation (presentation). EACL Workshop on Language Technology and Resources for Cultural Heritage, Social Sciences, Humanities, and Education, Athens, Greece, March 30, 2009.
  56. Evaluation of pairwise string alignment methods (presentation). Computational Linguistics in the Netherlands 19, Groningen, January 22, 2009.
  57. Dialect pronunciation comparison using the Goeman-Taeldeman-Van Reenen-project data (presentation). Computational Linguistics in the Netherlands 17, Leuven, Belgium, January 12, 2007.
  58. Parsing partially bracketed input (presentation). Computational Linguistics in the Netherlands 16, Amsterdam, December 16, 2005.
  59. Gabor filtering augmented with surround inhibition for improved contour detection by texture suppression (poster presentation). 27th Annual Meeting of the European Conference on Visual Perception, Budapest, Hungary, August 22 - 26, 2004.

 
 

 
 

 
 

 
 

Outreach

SPRAAKLAB!

As of February 2021, we have a mobile laboratory available for our outreach initiatives and conducting research in the field: SPRAAKLAB. SPRAAKLAB has all the facilities necessary for collecting high-quality data and running various types of experiments in linguistics: from acoustic and articulatory data collection to eye-tracking and EEG using portable equipment. Below you can see the launch video of SPRAAKLAB. This launch was covered by various news media, including RTV Noord (see News coverage, below).

Lowlands Science 2019

In August 2019, Dr. Gregory Mills and I investigated how language evolves and changes using a interactive game between two players. It was an incredible experience and we were able to collect speech production data for about 75 pairs of speakers during only three days! Our participation was made possible through financial contributions of the University of Groningen, the Young Academy Groningen and the Groningen University Fund. Below you can see an impression of this event. The event was covered by various news media, including NPO Radio 1 (see News coverage, below).

Lowlands Science 2018

In August 2018, we investigated the influence of alcohol on native and non-native speech using ultrasound tongue imaging. It was an incredible experience and we were able to collect speech production data for about 150 speakers during only three days! Our participation was made possible through financial contributions of the University of Groningen, the Young Academy Groningen and the Groningen University Fund. Below you can see an impression of this event. The event was covered by various national news media, including NPO Radio 1 (see News coverage, below).

Seeing your tongue move

We enjoy demonstrating how we collect data on tongue and lip movement during speech. If you'd like a demonstration at your school or event, please contact me. Below you can see an impression of my team at the Experiment Event for children organized by De Jonge Akademie, the NS, the Spoorwegmuseum, and Quest Junior.

Comic about my research

Through a project grant of De Jonge Akademie, I was able to create a comic about my research (designed and drawn by Lorenzo Milito and Ruggero Montalto). You can view the comic below or download it here for free. Please contact me if you would like to receive a printed copy of the Dutch version of the comic (as long as supplies last).

The comic itself

Presentations for the general public

  1. Panel member: Kunnen podcasts dialect in stand houden? (invited), Podcastfestival Groningen, Groningen, September 18, 2020.
  2. Van Old noar Jong (invited), Dag van de Grunneger Toal, Groningen, March 16, 2017.
  3. Taalvariatie en taalverandering in Nederland (invited), CSG Guido de Brès, Amersfoort, March 10, 2017.
  4. My career as a scientist (invited), KEI to your future event, Groningen, August 16, 2016.
  5. Taalvariatie en taalverandering in Nederland (invited), Theatre festival Oerol, Terschelling, June 13, 2016.
  6. Taalvariatie op de tong, NWO Bessensap, Amsterdam, June 10, 2016.
  7. Het verstrijken van de taal, De Jonge Akademie interscience symposium "Tijd", Amsterdam, April 4, 2016 [with John Nerbonne].
  8. Van dialecten tot accenten: variatie en verandering in uitspraak en tongbewegingen, Nacht van de Kunst en Wetenschap (pop-up lecture), Groningen, June 6, 2015.
  9. Talkshow guest (invited), Stand van Stad, Groningen, September 28, 2014.

Popular science publications

  1. "Wie zeggen het vaakst EUHM? Jongens of meisjes?", Science box, Experiment Event, De Jonge Akademie, 2018.
  2. Several contributions (with others), Young Scientist Wetenschapskalender 2018, New Scientist.
  3. Martin & Emma investigate the Dutch dialect landscape, comic, The Young Academy, 2017. Available at http://www.martijnwieling.nl/comic.
  4. Martin & Emma onderzoeken het Nederlandse dialectlandschap, comic, De Jonge Akademie, 2017. Available at http://www.martijnwieling.nl/strip.
  5. "Gebruiken mensen hun ogen om te luisteren?", Wetenschapskalender kids 2017, New Scientist.
  6. Dialectometrische indeling van de Nederlandse dialecten (with Peter Kleiweg and John Nerbonne), Nicoline van der Sijs (ed.) Dialectatlas van het Nederlands, Prometheus Bert Bakker, Amsterdam, pp. 60-61, 2011.

News coverage of my research

About Low Saxon / Groningen

  1. Martijn Wieling: la bellezza delle variazioni linguistiche (TV), RAI Cultura (Italy), October 27, 2019.
  2. Deze professor kan je vertellen hoe je dialect eruit ziet (online), Dagblad van het Noorden, October 20, 2019.
  3. Interview about Van Old noar Jong (radio), Groningen 1, July 29, 2019.
  4. News item about Van Old noar Jong (radio), NPO Radio 1: De Taalstaat (11:12:40), July 27, 2019.
  5. Google helpt om jongeren het Gronings bij te brengen (newspaper), Dagblad van het Noorden, July 23, 2019.
  6. Bijdrage 30.000 euro voor Groningse game basisonderwijs van Google (online), Groninger Internet Courant, July 22, 2019.
  7. Dertigduizend euro van Google voor stimulering Groningse taal (online), OOG, July 22, 2019.
  8. Techgigant Google helpt om de Groningse streektaal spelenderwijs Van Old noar Jong te brengen (online), Algemeen Dagblad, July 22, 2019.
  9. Techreus stopt 30.000 euro in onderwijsproject Groningse taal (online), NOS.nl, July 22, 2019.
  10. Google stopt 30.000 euro in een Gronings taalproject (radio), NPO Radio 1 nieuws, 16:03, July 22, 2019.
  11. Google investeert 30.000 euro in onderwijsapplicatie voor Groningse taal (online), NU.nl, July 22, 2019.
  12. Google steekt geld in app om kinderen enthousiast te maken voor het Gronings (radio), RTV Noord: Babette op Noord (10:15), July 22, 2019.
  13. 'Onderzoek doen naar taal is echt geweldig omdat het continu in beweging is' (newspaper), Algemeen Dagblad, May 4, 2019.
  14. Live Radio interview about my research at the Dag van de Groninger Taal (radio), RTV Noord, March 16, 2019.
  15. Het Gronings brengt mensen op een positieve manier bij elkaar (newspaper), Dagblad van het Noorden, March 2, 2019.
  16. Interviews om de Groningse taal van oud naar jong door te geven (newspaper), Dagblad van het Noorden, January 28, 2019.
  17. Levend Gronings oogsten voor educatieve game (newspaper), Nederlands Dagblad, January 23, 2019.
  18. Interview about the Groningen education game with my PhD student Martijn Bartelds (online), RTV Noord, January 22, 2019.
  19. Plof, mous en blaauwe doeven, blaauwe jongen in 't Klokhoes (online), RTV Noord, January 22, 2019.
  20. Live TV interview about the Groningen education game (TV), RTV Noord, January 22, 2019.
  21. Interview about the Groningen education game (radio), RTV Noord: Karel op Noord, January 21, 2019.
  22. Initiatief om gebruik Groninger taal te stimuleren (online), Noorderkrant, January 21, 2019.
  23. Is het nou 'hoes' of 'huus'? Nieuwe mobiele game gaat het kinderen leren (online), RTV Noord, January 21, 2019.
  24. 'Ik wil dat kinderen het Gronings meer gaan waarderen' (online), RTV Noord, December 20, 2018.
  25. Interview about my professorship (radio), RTV Drenthe, September 19, 2018.
  26. Martijn Wieling nieuwe hoogleraar Groningse taal en cultuur (online), Dagblad van het Noorden, September 18, 2018.
  27. Mensen moeten zich gaan realiseren dat het mooi is als je de streektaal spreekt (radio), RTV Noord, September 18, 2018.
  28. Martijn Wieling biezunder hoogleroar Grunneger toal en cultuur (online), RTV Noord, September 17, 2018.

About SPRAAKLAB

  1. RUG docht yn ridend lab Ûndersyk nei Fryske dialekten (radio), Omrop Fryslân, February 22, 2021.
  2. RUG wil taalkundig onderzoek boost geven met rijdend laboratorium (online), RTV Drenthe, February 17, 2021.
  3. Rijdend 'Spraaklab' gaat dialecten en articulatie onderzoeken (online), RTV Noord, February 17, 2021.
  4. Rijksuniversiteit Groningen neemt rijdend laboratorium in gebruik voor taalkundig onderzoek (online), Dagblad van het Noorden, February 17, 2021.

About Lowlands Science

  1. Biertje op? Schakel over naar een tweede taal! (online), NewScientist, September 21, 2020.
  2. Een nieuwe taal creëren tijdens Lowlands (online), Kennislink, August 22, 2019.
  3. Ki ka koe ki - Hoe ontstaat een taal? (radio), NPO Radio 1, August 22, 2019.
  4. Groningse wetenschappers op zoek naar bovennatuurlijke krachten op popfestival Lowlands (newspaper), Dagblad van het Noorden, August 16, 2019.
  5. Lowlands is een prachtlab vol enthousiaste proefkonijnen (newspaper), Trouw, August 16, 2019.
  6. Zeg ik a, dan zeg jij...? (online), NewScientist, August 2, 2019.
  7. NU.nl checkt dagelijks berichten op betrouwbaarheid. Bewering: "Je spreekt een vreemde taal beter na het drinken van alcohol." (online), NU.nl, November 9, 2018.
  8. Je kunt proefpersonen in een universiteit niet zomaar vijf biertjes laten drinken (online), ScienceGuide, August 24, 2018.
  9. Taalonderzoek tussen de Lowlands-optredens (online), Kennislink, August 23, 2018.
  10. RUG-wetenschappers onderzoeken op Lowlands of je met alcohol op beter bent in een vreemde taal (newspaper), Dagblad van het Noorden, August 20, 2018.
  11. 150 Lowlandsbezoekers lallen grenzeloos met Martijn Wieling (press release), University of Groningen, August 20, 2018.
  12. Interview about our Lowlands Science study (radio), RTV Noord: Spits op Noord, August 20, 2018.
  13. Interview about our Lowlands Science study (tv), RTV Noord: Noord Vandaag, August 20, 2018.
  14. Onderzoek op Lowlands: helpt alcohol bij taalgevoel? (newspaper), De Telegraaf, August 18, 2018.
  15. Live interview at Lowlands Science (radio), Omroep Flevoland, August 17, 2018.
  16. Veldonderzoek op Lowlands: spreek je beter Engels met een slok op? (radio), NPO Radio 1, August 17, 2018.
  17. Babbelen dronken Lowlandsgangers vlotter Engels? (online), NOS op 3, August 17, 2018.
  18. Met een drankje op spreek je veel beter een vreemde taal (radio), FUNX, August 13, 2018.
  19. Spraakecho met dubbele tong (newspaper), Dagblad van het Noorden, August 9, 2018.
  20. Spreekt een Nederlander met een slok op vloeiend(er) Engels? (newspaper), Trouw, August 8, 2018.
  21. Does being drunk improve your foreign language skills? (online), The Northern Times, August 8, 2018.
  22. Interview about Lowlands Science (radio), NPO Radio 2: Rabbering Laat, August 6, 2018.
  23. Ben je beter in een vreemde taal als je dronken bent? (online), Dagblad van het Noorden, August 6, 2018.
  24. Interview about Lowlands Science (radio), RTV Noord: Babette op Noord, August 3, 2018.
  25. Dubbele tong in beeld (online), NewScientist, July 31, 2018.
  26. Engels lallen op Lowlands (online), De Telegraaf, July 17, 2018.
  27. Interview about Lowlands Science (radio), Omroep Flevoland: Nieuws, June 21, 2018.
  28. Grenzeloos lallen met Martijn Wieling op Lowlands Science (press release), University of Groningen, June 21, 2018.

About my comic

  1. Taalwetenschapper verstript zijn onderzoek (newspaper), Dagblad van het Noorden, December 8, 2017.
  2. Wetenschap als stripavontuur (online), Universiteitskrant, December 6, 2017.
  3. RUG onderzoeker presenteert onderzoek in stripvorm (TV), OOG TV, December 4, 2017.
  4. Een strip over dialectonderzoek (online), Neerlandistiek, December 4, 2017.
  5. Strip over dialectonderzoek Martijn Wieling (press release), University of Groningen, December 4, 2017.
 

About articulography

  1. Onderzoek: Engels spreken met een echo-apparaat onder de kin (newspaper), Dagblad van het Noorden, November 13, 2018.
  2. Noordelijk dialect praat je achter in de mond (online), Neerlandistiek, January 31, 2017.
  3. Prijs voor tongbewegingen (online), Kennislink, July 27, 2016.
  4. Tongpositie verklaart buitenlands accent (newspaper), Dagblad van het Noorden, September 5, 2015.
  5. Hoe bewegen tong en lippen bij het spreken? (magazine), New Scientist, September 1, 2015.
  6. Tongpositie verklaart buitenlands accent (newspaper), Het Parool, August 29, 2015.
  7. Interview (radio), NPO Radio 1: Nieuwsshow, May 16, 2015.
  8. Interview (radio), RTV Emmen: Call it a day, May 13, 2015.
  9. Interview (radio), NPO Radio 1: WNL - Nog steeds wakker, May 13, 2015.
  10. Interview (radio), RTV Noord Holland: Spitstijd, May 12, 2015.
  11. Het dialectverschil zit 'm in de tong (TV), RTV Noord: Noord Vandaag, May 12, 2015.
  12. Dialectverschillen zien (TV), Omproep Max (NPO 2): Hallo Nederland & Tijd voor Max, May 12, 2015.
  13. Interview (radio), Simone FM: De Vos is Los!, May 12, 2015.
  14. Dialectverschil komt door de tong (TV), RTV Drenthe, Drenthe Nu, May 12, 2015.
  15. Dialectverschil heeft alles te maken met de tong (radio), NPO Radio 5: Plein 5, May 12, 2015.
  16. Dialect is niet alleen te horen maar ook te zien (radio), BNR Nieuwsradio: BNR B.L.T., May 12, 2015.
  17. Het dialectverschil zit 'm in de tong (radio), RTV Noord: Vroeg op Noord, May 12, 2015.
  18. Interview (radio), Q-music: Mattie en Wietze, May 12, 2015.
  19. Groningse tong staat anders dan een Gelderse (online), Nederlands Dagblad, May 12, 2015.
  20. Dialecten beginnen bij de tong, waarschijnlijk ook in Amsterdam (online), Het Parool, May 12, 2015.
  21. Dit is waarom jouw Engels niet goed klinkt (online), NOS op 3, May 12, 2015.
  22. Nieuw gezicht (newspaper), De Volkskrant, May 9, 2015.
  23. Wetenschap: de mysteries van de spraak (radio), NPO Radio 1: NOS - Wetenschap op woensdag, April 8, 2015.
  24. Experiment met de articulograaf (online), Universiteitskrant, March 31, 2014.
  25. Revealing the tip of the... tongue (newsletter), BCN Newsletter, March 1, 2014.
  26. Tong en lippen bepalen uitspraak (online), Unifocus, January 8, 2014.
  27. 'Ik heb meteen een sollicitatie afgezegd' (online), Universiteitskrant, September 2, 2013.
  28. Drent onderzoekt hardheid 'g' in Ter Apel (newspaper), Dagblad van het Noorden, March 7, 2013.
  29. Hoe hard is de harde g precies in Ter Apel? (newspaper), Dagblad van het Noorden, March 6, 2013.
  30. Plat praten met sensor op de tong (newspaper), Dagblad van het Noorden, March 5, 2013.

About the critical period in second language acquisition

  1. There is no critical period for learning a second language, kids just have more free time and motivation (online), Medical Daily, February 9, 2016.
  2. At what age is it easiest to learn a second language? (online), The Conversation, February 8, 2016.
  3. The best age to learn a second language (online), The Independent, February 8, 2016.
  4. Geen kritische periode voor leren tweede taal (online), Kennislink.nl, February 5, 2016.
  5. Nieuw onderzoek: geen harde leeftijdsgrens voor het leren van grammatica (online), Genootschap Onze Taal, January 19, 2016.

About the UH/UM distinction

  1. Zeg eens 'ehm' (newspaper), De Standaard, January 6, 2017.
  2. De stille opmars van ...ehm (newspaper), NRC & nrc.next, January 5, 2017.
  3. Afscheid van 'eh' (online), Vrij Nederland (vn.nl), August 21, 2015.
  4. Uh, why do we say um? (online), Braindecoder, August 12, 2015.
  5. Wetenschap: de mysteries van de spraak (radio), NPO Radio 1: NOS - Wetenschap op woensdag, April 8, 2015.
  6. Verschil tussen 'eh' en 'ehm' (radio), NPO Radio 1: NOS - Met het oog op morgen, February 8, 2015.
  7. Why we are saying 'uh' less and 'um' more (online), BBC, February 8, 2015.
  8. Are we witnessing the death of 'uh'? [...] (radio), Public Radio International, February 5, 2015.
  9. Things that make you go 'um' (online), The Atlantic, November 17, 2014.
  10. Zeg eens uh en ik zeg wie je bent (newspaper), De Morgen, October 8, 2014.
  11. UH / UM in Norwegian (online, guest post), Language Log, October 8, 2014.
  12. Trending in the Media: Um, not exactly... (online), Language Log, October 7, 2014.
  13. Stuck for words? How saying 'um' or 'er' in conversation [...] (online), Daily Mail, October 6, 2014.
  14. Men are from 'er' and women are from 'um' [...] (online), Daily Mail, October 6, 2014.
  15. Ah: Sounds to signal hesitation are part of our linguistic heritage (online), The Times, October 6, 2014.
  16. Um or er: which do you, um, use more in, er, conversation? (online), The Guardian, October 6, 2014.
  17. To um or to er? Studies probe how brains fill the speech-thought gap (online), The Times, October 4, 2014.
  18. UM / UH in German (online, guest post), Language Log, September 29, 2014.
  19. Um and Uh in Dutch (online, invited guest post), Language Log, September 16, 2014.

(Note that especially the English news coverage in 2014 got many details wrong, see this Language Log post.)

About dialectometry

  1. New linguistic tools can predict your dialect characteristics (online), LSA press release, September 24, 2014.
  2. Uitspraakverschillen (newspaper), Leeuwarder Courant, September 17, 2011.

Miscellaneous

  1. Robot weet welke uitspraak het hof zal doen (newspaper), NRC, December 30, 2020.
  2. Computersysteem voorspelt EHRM-uitspraken (online), Mr. Online, December 14, 2020.
  3. Mis je sociaal contact tijdens je werk? Met dit virtuele 'game'-kantoor maakt thuiswerker Martijn Wieling zijn baan in coronatijd weer leuk (newspaper), Dagblad van het Noorden, November 17, 2020.
  4. Groningse onderzoekers vragen coronasteun: Voorkom een verloren generatie (radio), RTV Noord, July 27, 2020.
  5. Erken en waardeer solidariteit in tijden van crisis (online), ScienceGuide, April 1, 2020.
  6. Geef niet alleen geld aan supersterren (newspaper), NRC, February 4, 2019.
  7. De roze bril van wetenschapsminister Van Engelshoven (online), NRC, February 3, 2019.
  8. Interview: Promotiestudent blijft de meningen verdelen (magazine), Onderzoek Nederland, November 23, 2018.
  9. Interview: How can universities support open science? (online), UG Open Access newsletter, November 6, 2018.
  10. Maak alle promovendi beurspromovendus: Naar een houdbaar en beter promotiestelsel (online), ScienceGuide, November 5, 2018.
  11. Opinie: Naar een rechtvaardig promotiestelsel (online), Universiteitskrant, October 31, 2018.
  12. Waarom hoogleraren en docenten vandaag een rood vierkantje dragen (online), NOS, September 3, 2018.
  13. Jonge onderzoekers in de sociale- en geesteswetenschappen vallen buiten de boot: subsidies beperkt (newspaper), de Volkskrant, July 4, 2018.
  14. NWO-beurs: extensie van extensieregel' (online), U-Today, May 4, 2018.
  15. NWO helpt ook vaders zorgen (online), Universiteitskrant, May 1, 2018.
  16. NWO geeft voortaan alle ouders langer de tijd voor een aanvraag (online), Science Guide, April 30, 2018.
  17. Datasets beschikbaar via RUG onderzoeksdatabase (online), Pictogram, March 1, 2018.
  18. Opinie: "Zorg zelf voor diversiteit uraad!" (online), Universiteitskrant, February 7, 2017.
  19. Martijn Wieling wint prestigieuze European Young Researchers Award (press release), University of Groningen, May 4, 2016.
  20. European Young Researchers Award: the EYRA 2016 laureates (online), EuroScience, May 3, 2016.
  21. Promoveren werkt, maar hoe lang nog? (online; with Sicco de Knecht), ScienceGuide, April 19, 2016.
  22. The future of science: Harder, better, faster? (newsletter), BCN Newsletter, December 1, 2015.
  23. SZW benadeelt jong talent in R&D (online), ScienceGuide, October 23, 2015.
  24. Snel een aardbeving detecteren met Twitter (magazine), I/O Magazine, September 1, 2015.
  25. Ook niet-hoogleraren moeten promotor kunnen zijn (newspaper), NRC, April 28, 2015.
  26. Presentation at the general meeting of De Jonge Akademie (online), De Jonge Akademie, March 31, 2015.
  27. The fruits of your labors (online), Language Log, July 26, 2013.
  28. Rating American English accents (online), Language Log, May 19, 2012.

Miscellaneous

Some interests outside of academia

Some useful resources

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