Department of Linguistics and Languages at McMaster University

04/01/2026

We are pleased to invite students, alumni, faculty, and friends of the Department of Linguistics and Languages to the 2026 Student Research Day on April 8, 2026, 9:00am-4:00pm in Chester New Hall 104.

This year’s Student Research Day will feature presentations and posters that reflect the wide range of research being done in the Department of Linguistics and Languages by undergraduate and graduate students, and a keynote talk by Büşra Marşan and Jasper Jian, PhD candidates at Stanford University, titled “Turkish comitative (non-)coordination: A new view on hierarchy effects.”

View the full program and abstract book:https://readlab.humanities.mcmaster.ca/wp-content/uploads/2026/04/Student-Research-Day-2026-Program.pdf

We hope you will join us for what promises to be an engaging day celebrating language research!

03/27/2026

The Cognitive Science of Language lecture series talk will take place on Tuesday April 7, 12:30-2:20pm, LRW 2001. The lecture will be delivered by Dr. Freda Shi. Dr. Shi is an Assistant Professor in the Cheriton School of Computer Science at the University of Waterloo and a Faculty Member at the Vector Institute, where she also holds a Canada CIFAR AI Chair. She received her Ph.D. degree in Computer Science with distinction from the Toyota Technological Institute at Chicago, and was a visiting doctoral student in Brain & Cognitive Science at the Massachusetts Institute of Technology. Her research interests are in computational linguistics and natural language processing. Her work has been recognized by an Outstanding Paper Award at EMNLP 2025, nominations for the Best Paper Award at ACL 2019, 2021, and 2024, and, earlier, a Google PhD Fellowship and a Finalist Award for the Facebook Fellowship. Her research has been supported by Autodesk, CIFAR, MITACS, NSERC, OpenAI, and TD-Layer 6 Lab.

Title: The "Developmental Linguistics" in Language Models

Abstract: With the advancements of powerful large language models (LLMs) such as ChatGPT, Claude, and Gemini, there is an increasing interest in understanding how these models gradually acquire different linguistic skills throughout the learning process---a field we may call "computational developmental linguistics" with computational language models as the subjects. The anticipated impact of this line of research is twofold: first, it helps characterize the learning process of language models to inform the enhancements; second, findings in this area may lead to novel hypotheses regarding human language acquisition.
In this talk, I will first review current methodologies for studying developmental linguistics in language models. I will then present a case study from our group investigating how vision-language models acquire the skill of symbol grounding---the process of linking a linguistic form to its visual ground.

We are looking forward to seeing you!

01/13/2026

The Cognitive Science of Language lecture series talk will take place on Tuesday January 20, 12:30-2:20pm, LRW 2001. The lecture will be delivered by Dr. Sara A. Hart. Dr. Hart is the Canada Excellence Research Chair in Developmental Science and Professor of Psychology at the University of Waterloo, Canada. Broadly, her substantive research relates to understanding how and why people differ in their cognitive development, particularly focused on reading and math development. Most of her work to date has focused on using twin and genomic methods to understand the "nature" and "nurture" of child development. She examines the role of an individual’s genetic variants and contexts in predicting school achievement and intervention response. She also contributes to the field of meta-science, understanding how scientists do science, with a particular interest in supporting rigorous and reproducible developmental science. With colleagues, she built a data repository, LDbase, to support the data sharing and data access needs of scientists working in fields of developmental science related to education. Beyond research, she is passionate about training, translation of research, and advocating for equity deserving groups in science.

01/06/2026

Polish is apparently the optimal language for AI applications and a very interesting language for a linguist to know. Here is your chance to learn it!

12/06/2025

We are very sad to inform you about the passing of our retired colleague and professor of German, Gerry Chapple. Our former students may remember Gerry's wit and enthusiasm. He will be missed by all who knew him. The following information is taken from the funeral home website at https://www.burnett-white.com/obituaries/Clement-Gerald-Chapple?obId=46288942

Gerald was born in 1937 in Canada. In Hamilton, Ontario, Gerald graduated from McMaster University in 1960 with a BA in German and French. Inspired by working at the Canadian Pavilion at the 1958 Brussels World Fair and by studying at the University of Munich, Gerald went on to earn his PhD in German Literature from Harvard University.

Over his 36 years as a professor at McMaster University, Gerald shared with students and colleagues his lifelong enthusiasm for language, literature, philosophy, and culture, focusing on German while drawing on his knowledge of French, Italian, Ancient Greek, and Latin. A prolific translator of German prose and poetry into English, he just last month finished his tenth crime novel by Swiss-Canadian author Bernadette Calonego.

Jerry’s interests ranged widely: birds counted daily for Cornell Ornithology, plants and trees always known by Latin names, butterflies and insects photographed in detail, classical music instantly recognized by composer and title, Dave Brubeck, opera, Kandinsky, Tom Lehrer, Monty Python, authors from Elizabeth Bowen to Bertolt Brecht, long-form jokes, and his beloved Blue Jays, Montréal Canadiens, and Buffalo Bills.

View Gerald Chapple's obituary, contribute to their memorial, see their funeral service details, and more.

11/14/2025

The Cognitive Science of Language lecture series talk will take place on Tuesday November 25, 3:30-5:20pm, LRW 2001. The lecture will be delivered by Dr. Blair Armstrong. Dr. Armstrong is an Assistant Professor in the Department of Psychology at the University of Toronto Scarborough. Their primary research interests relate to the cognitive and neural representations, processes, and learning mechanisms underlying word comprehension and semantic memory. This work largely concerns developing theories of how ambiguous words are comprehended, the source of the similarities and differences between written and spoken word comprehension, how learning mechanisms lead to the emergence of cross-linguistic differences in lexical processing, and how newly-learned words are integrated into the lexical system. Their work focuses on developing explicit mechanistic accounts of these cognitive systems. This work is informed by tightly coordinated computational modeling using neural networks and by empirical investigations using a range of behavioral and electrophysiological techniques. They are also interested in how computational algorithms can improve experimental methodologies such as stimulus selection, speech onset detection, and data analysis.

Title: : Neural Network Insights Into Lexical Ambiguity

Abstract: Most words are lexically ambiguous and denote different meanings in different contexts. For example, BANK can denote a financial institution or the edge of a river, and CHICKEN can denote an animal or its meat. As such, understanding lexical ambiguity is fundamental to any comprehensive theory of word and discourse comprehension. However, research in this area must overcome several key challenges related to the multifaceted nature of lexical ambiguity and how processing ambiguous words varies across experimental tasks.
In my talk, I will highlight how coordinated computational research using neural networks, in concert with experimental work, can help advance the theoretical understanding of lexical ambiguity on a number of fronts. I will first discuss how a neural network model that incorporates specific neurobiological constraints can explain the dynamic nature of meaning activation. This model reveals the processing time-course for ambiguous words which either do (polysemes) or do not (homonyms) have related meanings, explaining divergent experimental results from different tasks. Next, I will report recent work using a Large Language Model (LLM) to understand regular polysemy, sets of polysemes that share the same relationship between their meanings, such as CHICKEN and LOBSTER both referring to an animal or its meat. This work indicates that the degree of shared structure varies across different regular relationships (e.g., animal/meat vs. location/organization), potentially reflecting a “regularity continuum”. Furthermore, these effects are not necessarily explained by the degree of relatedness amongst word meanings, suggesting that a different principle may influence the emergence of regular polysemes. I will then illustrate how neural network models can be used to identify key principles that govern why individual word senses are acquired in particular orders during development. Finally, time permitting, I illustrate how experimental research in lexical ambiguity can serve as a foil for exploring the impact of stimulus re-use on generalizability of experimental findings in psycholinguistics and beyond.
Overall, this body of work promotes the value of considering learning, representation, and processing as intertwined constructs, grounded in domain-general theory and explicit computational models, in advancing theories of lexical ambiguity.


We are looking forward to seeing you at the event!

11/11/2025

Our beautiful campus in the fall

11/09/2025

The Cognitive Science of Language lecture series talk will take place on Tuesday November 11, 3:30-5:20pm, LRW 2001. The lecture will be delivered by Dr. Annie En-Shiun Lee. Professor Annie En-Shiun Lee is an assistant professor at Ontario Tech University and the University of Toronto (status-only). Professor Lee’s goal is to make language technology as inclusive and accessible to as many people as possible, under the institutional vision “Tech with a Conscience”. Professor Lee directs the Lee Language Lab (L^3) with research focusing on multilingual and multicultural natural language processing and large language models, especially in the adoption of technology and its usability for disenfranchised or underserved groups at risk of being left behind the digital divide. Professor Lee’s research has been published in Nature Digital Medicine, ACM Computing Survey, ACL (EACL, NAACL, ACL), SIGCSE, IEEE TKDE, and Bioinformatics. Dr. Lee is the demo co-chair for NAACL 2024 and has received numerous recognitions, including Outstanding Paper Award and Best Theme Paper Award at NAACL 2025, Audience Award at Teaching NLP 2024, ARIA Spotlight Award for MScAC 2024, as well as nominated for Tim McTiernan Student Mentorship Award 2025, and Women in AI Researcher of the Year Award 2025.

Title: Bridging the World with Words: Multilingual and Multicultural Natural Language Processing

Abstract: Despite the rapid advances in Large Language Models (LLM), research efforts have historically focused disproportionately on high-resource languages, particularly English, leaving over 7,000 living languages underserved. We address the fundamental challenge of bridging the gap of low-resource language (LRL) translation in multilingual language models. Low-resource languages are typically characterized by a scarcity of both unlabeled and labeled data, as well as limited tools and models. This talk explores strategies aimed at bridging the gap of low-resource language (LRL) translation in multilingual models, where LRLs are characterised by a limited scarcity of both unlabeled and labelled data, as well as limited tools and models. The talk will detail the importance of quantifying linguistic distance to improve the robustness and predictability of multilingual model performance. We introduce our improvements to the World Languages Database, URIEL+, an expanded linguistic knowledge base that addresses issues like low feature coverage, lack of morphological data, and ambiguous distance calculations. URIEL+ significantly expands typological coverage for nearly 2,900 languages and supports 361 new low-resource languages. By utilising this enhanced resource, our work on Open Toolkits & Models demonstrates that integrating linguistic distance metrics and dataset information (ProxyLLM) leads to models that are more robust and consistently more accurate, yielding performance increases on downstream tasks by up to 50%. Success in LRL research requires widespread cooperation through Community Collaboration, we detail our projects in Creating New Datasets for linguistic and cultural diversity. We highlight dataset collaborations with grassroots groups like WorldCuisines with Southeast Asia Crowd (recognized as a "best paper"), IrokoBench with Masakhane (recognised as an "outstanding paper"), and Error Annotation in Machine Translations of Chinese Dialects. Lastly, we discuss developing language tools such as Language Learning Apps (Language Education/ATAIIGI), the Annotation Correction App (Annotation Correction), and materials focused on Teaching Multilinguality (recognized with an Audience Award).

We are looking forward to seeing you at the event!

11/07/2025

The Cognitive Science of Language lecture series talk will take place on Tuesday November 11, 3:30-5:20pm, LRW 2001. The lecture will be delivered by Dr. Annie En-Shiun Lee. Professor Annie En-Shiun Lee is an assistant professor at Ontario Tech University and the University of Toronto (status-only).

Professor Lee’s goal is to make language technology as inclusive and accessible to as many people as possible, under the institutional vision “Tech with a Conscience”. Professor Lee directs the Lee Language Lab (L^3) with research focusing on multilingual and multicultural natural language processing and large language models, especially in the adoption of technology and its usability for disenfranchised or underserved groups at risk of being left behind the digital divide. Professor Lee’s research has been published in Nature Digital Medicine, ACM Computing Survey, ACL (EACL, NAACL, ACL), SIGCSE, IEEE TKDE, and Bioinformatics. Dr. Lee is the demo co-chair for NAACL 2024 and has received numerous recognitions, including Outstanding Paper Award and Best Theme Paper Award at NAACL 2025, Audience Award at Teaching NLP 2024, ARIA Spotlight Award for MScAC 2024, as well as nominated for Tim McTiernan Student Mentorship Award 2025, and Women in AI Researcher of the Year Award 2025.

Title: Bridging the World with Words: Multilingual and Multicultural Natural Language Processing

Abstract: Despite the rapid advances in Large Language Models (LLM), research efforts have historically focused disproportionately on high-resource languages, particularly English, leaving over 7,000 living languages underserved. We address the fundamental challenge of bridging the gap of low-resource language (LRL) translation in multilingual language models. Low-resource languages are typically characterized by a scarcity of both unlabeled and labeled data, as well as limited tools and models. This talk explores strategies aimed at bridging the gap of low-resource language (LRL) translation in multilingual models, where LRLs are characterised by a limited scarcity of both unlabeled and labelled data, as well as limited tools and models. The talk will detail the importance of quantifying linguistic distance to improve the robustness and predictability of multilingual model performance. We introduce our improvements to the World Languages Database, URIEL+, an expanded linguistic knowledge base that addresses issues like low feature coverage, lack of morphological data, and ambiguous distance calculations. URIEL+ significantly expands typological coverage for nearly 2,900 languages and supports 361 new low-resource languages. By utilising this enhanced resource, our work on Open Toolkits & Models demonstrates that integrating linguistic distance metrics and dataset information (ProxyLLM) leads to models that are more robust and consistently more accurate, yielding performance increases on downstream tasks by up to 50%. Success in LRL research requires widespread cooperation through Community Collaboration, we detail our projects in Creating New Datasets for linguistic and cultural diversity. We highlight dataset collaborations with grassroots groups like WorldCuisines with Southeast Asia Crowd (recognized as a "best paper"), IrokoBench with Masakhane (recognised as an "outstanding paper"), and Error Annotation in Machine Translations of Chinese Dialects. Lastly, we discuss developing language tools such as Language Learning Apps (Language Education/ATAIIGI), the Annotation Correction App (Annotation Correction), and materials focused on Teaching Multilinguality (recognized with an Audience Award).

We are looking forward to seeing you at the event!

10/04/2025

Good afternoon,

The Cognitive Science of Language lecture series talk will take place on Tuesday October 7, 3:30-5:20pm, LRW 2001. The lecture will be delivered by Dr. Diane Mézière. Dr. Mézière is a cognitive scientist currently working at the University of Turku. She obtained a joint PhD in cognitive science and linguistics from the IDEALAB international program at the universities of Sydney (Australia) and Groningen (The Netherlands). Her work focuses on using eye-tracking to better understand reading comprehension processes, and explores the possibly of using eye-tracking to develop valid and reliable measures of reading skills.

Title: Can eye movements be used to measure reading comprehension ability?

Abstract: The ability to understand written text is critical in our literate society. However, in recent years we have seen a general decline in reading skills all over the world. An important step in understanding and trying to remedy this issue is the development of reliable assessments of reading comprehension skills. In the last decades however, the validity of reading comprehension assessments has been brought into question and researchers have worked on possible alternative methods to measure reading comprehension. One such method is the use of eye-tracking, as it provides an ecologically-valid measure of the reading process. In this talk, the relationship between eye-movement measures and reading comprehension skills is discussed, and the possibility of developing a reading measure based on eye-movement behaviour is explored.

We are looking forward to seeing you at the event!

09/14/2025

Dear colleagues!

The Cognitive Science of Language lecture series talk will take place on Tuesday September 16, 3:30-5:20pm, LRW 2001. The lecture will be delivered by Dr. Alice Corr. Dr. Corr is an Associate Professor in the Department of Modern Languages at the University of Birmingham, England, where she specializes in the comparative morphosyntax, dialectology, and history of the Romance languages. Focusing on non-standard synchronic and historical variation in varieties originating in the (Western) Iberian Peninsula, her research seeks to reconcile theoretical and empirical work in this area with conceptual insight drawn from outside conventional disciplinary boundaries. She is author of The Grammar of the Utterance: How to Do Things with Ibero-Romance (OUP, 2022) and co-editor, with Anna Pineda, of Theoretical Linguistics in the Pre-University Classroom (OUP, 2023).

Title: : Diasporic languages and linguistic theory: insights from Judeo-Spanish

Abstract: Minoritized languages often stretch the limits of what our theoretical frameworks can capture. In this talk, I suggest that diasporic languages such as Judeo-Spanish offer a privileged vantage point from which to probe these limits. Drawing on ongoing field and archival research, I discuss how Judeo-Spanish grammatical variation and change is differentially shaped by structural and environmental factors. Some patterns appear anomalous under standard structuralist assumptions, but become legible once sociohistorical and sociocultural dimensions are taken into account. These case studies generate new insights into the ways in which grammatical structures are synchronically and diachronically shaped by—and impervious to—the complex social environments in which they are embedded. I suggest that these findings open up new possibilities for structuralist analysis, and invite us to broaden how the relationship between grammar and its social environment is conceived in linguistic theory.

We are looking forward to seeing you at the event!