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Cambridge Language Sciences

Interdisciplinary Research Centre
Cambridge Language Sciences Annual Symposium 2020 What Next? Future Directions in Language Research

The Cambridge Language Sciences Annual Symposium is an annual meeting of minds, bringing together language scientists of all disciplines from the University of Cambridge and beyond. The theme of this year's event is Future Directions in Language Research.

This year, in addition to the live event on 17 November, we are excited to be hosting the Annual Symposium posters, along with recordings of the live plenary sessions, on Cambridge Open Engage, an early research site run by Cambridge University Press. The site will offer a place for delegates to access and discuss the talks and posters beyond the live event, and allow a wider research audience to reach and interact with the content.

REGISTER HERE - registration is open until 12 November 2020.



10:30-11:15 Revisiting perceptual categories in Flege's Speech Learning Model: insights from a deep learning-based approach for measuring phonetic similarity

Calbert Graham, Phonetics Laboratory, University of Cambridge

The Speech Learning Model (SLM) has become the dominant phonetic model that addresses the role the native language system (L1) plays in a second language (L2) learner’s ability to produce and perceive phonetic contrasts in their target language speech. The model assumes that how listeners categorise a phone in their L2 as compared to their L1 (i.e. as ‘identical’, ‘similar’, or ‘new’) will determine the success with which they will discriminate a given phonetic distinction. Phonetic similarity is therefore crucial to the SLM in predicting areas of difficulty in L2 perception and production.

However, the notion of similarity has not been adequately defined in the SLM. For example, the question of whether L1 and L2 sounds can be truly phonetically identical has not been adequately addressed in its development, leading to inconsistent findings depending on which pre-selected acoustic features (e.g. vowel formants, duration, spectral features, etc.) are used to compare segments.

In this talk I will report a vowel classification experiment involving a deep convolutional neural network (CNN) based on spectrogram pictures that provide a much wider range of information than a pre-selected set of acoustic features. The classification task was to determine the native language of speakers of different L1 backgrounds on the basis of their vowel production in English. In testing the assumptions of the SLM, we examined the putative relationship between acoustic (and perceptual) similarity and acquisition difficulty.

Results revealed that the characteristics of all target vowels, including those identified by SLM researchers as ‘identical’ in the L1 and L2 of a speaker, contributed to the significant discrimination between vowels produced by an L1 speaker and those produced by an L2 speaker. Furthermore, contra the SLM, expected differences between perceptual categories were not found, as vowels identified as ‘similar’ in the L1 and L2 were no more problematic than ‘identical’ or ‘new’ ones in the classification task.

We conclude that as a single phoneme is associated with an undefined range of successive articulatory events, modelling L1-L2 interactions requires a multidimensional approach to capture this vast variability in speech in a way that the broad and somewhat arbitrary approach of the SLM is unable to do. We also discuss limitations of this relatively new approach and directions for future research.

11:15-12.00  Speaker to be confirmed

13:00-13:30 Poster slam

One-minute talks by the poster presenters

Poster presenters will give a lightning talk during the plenary session to advertise their poster. Presenters will be given exactly one minute and one slide to let the audience know what their poster is about. 

13.30-14.30 Poster exhibition 

The poster session will showcase research being carried out within Cambridge Language Sciences with a particular focus on PhD students and postdocs and new and/or interdisciplinary research. It will feature a wide range of disciplinary perspectives relating to Language Sciences and is not restricted to this year's Symposium theme.

15:30-16:15 Social Signalling and Social Change: Inclusive Writing in French

Heather Burnett, Laboratoire de Linguistique Formelle, CNRS and Université de Paris

Gender inclusive writing ("écriture inclusive" EI) has long been the topic of public debates in France. Examples of EI for the word "students" are shown in (1).

(1) a. étudiant·e·s (point médian)
b. étudiant.e.s (period)
c. étudiants et étudiantes (repetition)
d. étudiant(e)s (parentheses)
e. étudiant-e-s (dash)
f. étudiantEs (capital)
g. étudiant/e/s (slash)
h. étudiant--e--s (double dash)

These debates have amplified since the Macron government prohibited the use of the point médian (1a) in official documents in 2017 (Abbou et al. 2018). In addition to being a point of disagreement between feminists and anti-feminists, EI is also controversial among feminists: it has many variants (1), who often disagree on which variant should be used (Abbou 2017).

In this talk, I argue that the source of many of these disagreements lies in the fact that French écriture inclusive has developed into a rich social signalling system: based on a quantitative study of EI in Parisian university brochures (joint work with Céline Pozniak (Burnett & Pozniak 2020)), I argue that writers use or avoid EI in part in order to communicate aspects of their political orientations. We show that these aspects involve writers' perspectives on gender, but also stances on issues unrelated to gender, such as (anti)institutionalism and support for the Macron government. I then outline a research programme for studying this signalling system from a formal perspective: following Burnett (2019), I show how we can use game-theoretic pragmatics to analyze EI's contribution to writers' political identity construction and the consequences that this has for its use as a tool for promoting gender equality and social change.


Abbou, J., Arnold, A., Candea, M., & Marignier, N. (2018). Qui a peur de l’écriture inclusive? Entre délire eschatologique et peur d’émasculation Entretien. Semen. Revue de sémio-linguistique des textes et discours, (44).
Abbou, J. (2017). (Typo) graphies anarchistes. Où le genre révèle l’espace politique de la langue. Mots. Les langages du politique, (1), 53-72.
Burnett, H. & C. Pozniak. (2020). Political Dimensions of Écriture Inclusive in Parisian Universities. Manuscript, Université de Paris.
Burnett, H. (2019). Signalling Games, Sociolinguistic Variation and the Construction of Style. Linguistics and Philosophy, 42(5), 419-450.

16:15-17:00 Cognitive and computational building blocks for more human-language language in machines (provisional title)

Josh Tenenbaum, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology (MIT)

Humans learn language building on more basic conceptual and computational resources that we can already see precursors of in infancy. These include capacities for causal reasoning, symbolic rule formation, rapid abstraction, and commonsense representations of events in terms of objects, agents and their interactions. I will talk about steps towards capturing these abilities in engineering terms, using tools from hierarchical Bayesian models, probabilistic programs, program induction, and neuro-symbolic architectures. I will show examples of how these tools have been applied in both cognitive science and AI contexts, and point to ways they might be useful in building more human-like language, learning and reasoning in machines.


Poster presentations

Teaching of Creativity in the English Language Classroom, Abie Chan

Linguistic capital and the Cambridge Admissions Interview, Daniel Weston

Working with Data from Real-World Corpora: A Case Study on Identifying Issues and Using Scalable Solutions, Itamar Shatz

Emergent grammatical systematicity in Tây Bồi (Vietnamese Pidgin French), Oliver Mayeux

‘Under the shadow of swords: The Path to Jihad’ - A Corpus-Based Critical Analysis of Religious Metaphors in Jihadist Magazines, Katie Patterson

Do you see the -ing in SMOYING? Reading proficiency might influence the way we process unfamiliar words,Julia Schwarz

Collecting the Teacher-Student Chatroom Corpus, Andrew Caines

Word Prosody in Khorchin Mongolian, Chenming Gao

Syntactic L1-Attrition and Re-Exposure, Alexander Cairncross

The causal role of language-specific brain regions in contextual updating of ambiguous word meanings, Lucy MacGregor

Tones and tone sandhi in Xiangshan Wu Chinese, Yibing Shi

Challenges to Speech Perception Impair Phonological Short-Term Memory, Harriet Smith

Syntactic Ambiguity: Meter, Rhyme and Lineation Effects, Andromachi Tsoukala

The Development of a Syntactic Awareness Task using Word-Order Correction Paradigm, Claudia Pik-Ki Chu

Vowel perception & production integration in Spanish/English bilinguals: an experimental study, Madeleine Rees

Focus production in Cantonese and its implication for prosodic typology, Kechun Li

Explaining the Mathematical Word Problem Performance of Multilingual Children in Hyderabad, India, Jodie Webber

Ontology for a Common Sense Knowledge Graph, Guy Aglionby

Interfacing sound, meaning and constraint: Neural infrastructure for incremental interpretation, Yuxing Fang

Neurobiological dynamics involved in processing long-distance dependencies, Benedict Vassileiou

Tracing the motivational dynamics of L3 learners: a multiple case study of four high- and low-proficiency undergraduates in the UK, Lixinhao Gao

Talk about mind and space: paternal and maternal contributions to school readiness,  Elian Fink


In addition to the live poster session on 17 November, posters will be available to view on Cambridge Open Engage from 10 November. 

We would like to thank James Algie ( and Yuchen Zong ( for organising the poster session this year. 



We gratefully acknowledge the support of Cambridge Assessment and Cambridge University Press in running this year's event.


Tuesday, 17 November, 2020 - 10:30 to 17:00
Event location: 
Online event - please register for details of how to join

What we do

Cambridge Language Sciences is an Interdisciplinary Research Centre at the University of Cambridge. Our virtual network connects researchers from five schools across the university as well as other world-leading research institutions. Our aim is to strengthen research collaborations and knowledge transfer across disciplines in order to address large-scale multi-disciplinary research challenges relating to language research.