Advanced Computation Methods for Linguists
Horaire:
lundi 13h à 16h
Instructeur:
E. Dunbar
Location:
Veuillez nous contacter.
Salle:
Veuillez nous contacter.
Description
Advanced Computational Methods for Linguists develops the outcomes of JFL1107H (Computational Methods for Linguists). In the first half of the course, students will get theoretically and practically acquainted with a breadth of contemporary computational methods in linguistics, such as word vectors, finite state machines, Gaussian mixture models, parsing algorithms, n-grams and textual association measures, and dimensionality reduction. These methods will be developed in relation to fundamental research topics in linguistics: syntax, semantics, phonetics, phonology, morphology, sociolinguistics, and language acquisition. Students will go in depth in the second half of the course with methods surrounding a topic selected by the instructor (for instance: studying lexical semantic variation, parsing algorithms in cognitive modeling, first and second-language speech perception).
Reading List
Kaplan, Ronald and Martin Kay. 1994. Regular models of phonological rule systems. Computational Linguistics 20.3: 331-378.
Heinz, Jeff (ed.). To appear. Doing Computational Phonology.
James, Gareth, Daniela Witten, Trevor Hastie, and Robert Tibshirani. 2013. An Introduction to Statistical Learning. New York: Springer.
Tunstall, Lewis, Leandro Von Werra, and Thomas Wolf. 2022. Natural Language Processing with Transformers. O'Reilly Media, Inc. 2022.
Goodfellow, Ian, Yoshua Bengio, and Aaron Courville. 2016. Deep Learning. MIT Press.
Dunbar, Ewan, Nicolas Hamilakis, and Emmanuel Dupoux. 2022. Self-supervised language learning from raw audio: Lessons from the Zero Resource Speech Challenge. IEEE Journal of Selected Topics in Signal Processing 16.6: 1211-1226.
Jurafsky, Dan and James H. Martin. To appear. Speech and Language Processing, 3rd ed.
Slaats, Sophie and Andrea Martin. 2023. What's surprising about surprisal. Psyarxiv Preprint.
Chandlee, Jane, and Jeffrey Heinz. 2018. Strict locality and phonological maps. Linguistic Inquiry 49.1: 23-60.
McCollum, Adam G., Eric Baković, Anna Mai, and Eric Meinhardt. 2020. Unbounded circumambient patterns in segmental phonology. Phonology 37.2: 215-255.
Dolatian, Hossep, and Jeffrey Heinz. 2020. Computing and classifying reduplication with 2-way finite-state transducers. Journal of Language Modelling 8.1: 179-250.
Burness, Phillip Alexander, Kevin James McMullin, and Jane Chandlee. 2021. Long-distance phonological processes as tier-based strictly local functions. Glossa: a journal of general linguistics 6.1.
Millet, Juliette, and Ewan Dunbar. 2022. Do self-supervised speech models develop human-like perception biases? arXiv preprint arXiv:2205.15819.
Schatz, Thomas, Naomi H. Feldman, Sharon Goldwater, Xuan-Nga Cao, and Emmanuel Dupoux. 2021. Early phonetic learning without phonetic categories: Insights from large-scale simulations on realistic input. Proceedings of the National Academy of Sciences 118.7: e2001844118.
Tuckute, Greta, Jenelle Feather, Dana Boebinger, and Josh H. McDermott. 2022. Many but not all deep neural network audio models capture brain responses and exhibit correspondence between model stages and brain regions. bioRxiv preprint.
Evaluation
|
Final project |
|
|
250 word idea and informal presentation |
5% |
|
1-2 page proposal and informal presentation |
10% |
|
Outline |
10% |
|
Final version |
20% |
|
Completed exercises (two series) |
30% |
|
Two paper presentations |
25% |