The following minicourses will be given on Thursday, January 3 at the LSA Annual Meeting in New York City.  Please sign up below for no more than one minicourse.

Neural Networks

Room: Central Park East
Time: 9:00 AM - 3:00 PM, with an hour break for lunch

What’s the buzz about neural networks in linguistics? This minicourse introduces the basic ideas behind neural networks from the ground up, beginning with a discussion of how computers represent language at the character and word level, and moving up from there. We illustrate each step of the way with examples of and discussion about real-world tasks from natural language processing and machine learning.

The course covers word- and character-level operations, such as morphological analysis, stemming, and categorization. From there, we introduce additional machine learning concepts using larger objects such as sentences and then corpora. We then jump from this foundation into a deep dive into both shallow and deep neural networks, from multilayer perceptrons to RecurrentNeural Networks (RNNs).



Katy McKinney-Bock, Oregon Health & Science University
Steven Bedrick, Oregon Health & Science University


Bayesian Phylogenetics for Linguists

Room: Central Park West
Time: 10:00 AM - 3:00 PM, with an hour break for lunch

This workshop provides an overview of Bayesian phylogenetics for linguists. The session will work through the components of an analysis: the type of data, the different models frequently used, and assumptions about language change. Topics to be covered will be drawn from tree estimation (constructing a tree from data), ancestral state reconstruction (inferring values of features at subgroup and root nodes), network construction (e.g. NeighborNets), visualizing results, dating, and detecting phylogenetic signal in a dataset, according to the interests of participants. The aim in the workshop is to give participants a conceptual understanding of Bayesian phylogenetics, rather than a ‘black box’ approach to applying software.

Note: Limited funding is available to cover the costs of this minicourse for students, unwaged persons, or indigenous scholars.  Contact the LSA for more details. 

Instructor: Claire Bowern, Yale University


Evaluating phonological structure through simulation and classification of phonetic data

Room: Lenox Ballroom
Time: 9:00 AM - 3:00 PM, with an hour break for lunch

As phonetic data have come to play an increasingly important role in evaluating phonological structure, methods for relating the continuous phonetic signal to discrete phonological categories have also become more sophisticated. This mini-course introduces an approach that leverages techniques in machine learning and signal processing to simulate and classify phonetic data in terms of phonological categories. Participants will be introduced to the computational toolkit developed in Shaw & Kawahara (2018). We will walk through application of the methodology to some common data problems, including assessing presence/absence of a tone based on the f0 trajectory and presence/absence of a vowel (c.f., open transition between consonants) based on the kinematics of tongue movements. Appropriate sample data from electromagnetic articulatography and data visualization tools will be provided along with scripts and documentation to support generalization to new datasets.

Shaw, J. A., & Kawahara, S. (2018). Assessing surface phonological specification through simulation and classification of phonetic trajectories. Phonology, 35(3), 481-522. doi:10.1017/S0952675718000131

Instructor:  Jason A. Shaw, Yale University


Teaching Linguistics

Room: Bowery
Time: 9:00 AM - 3:00 PM, with an hour break for lunch


Pedagogical training for those preparing to teach in higher education is often minimal or erratic, or focused on teaching adjacent subjects like composition or second language courses rather than linguistics proper. Even more, much of this instruction often focuses on course and program requirements, administration, and evaluation rather than student-centred pedagogical tools and approaches to incorporate into the classroom.

In this mini-course, participants (ABD to professor) will learn about the evidence-based instructional practices of active learning and service-based or experiential learning, as well as how to apply these practices in the classroom and in an online instructional environment. We will also introduce workshop participants to concepts from universal design for instruction in order to address issues of accessibility in the classroom. Workshop participants will take away from the workshop a sample lesson plan incorporating one or more of these techniques or approaches.

Instructor: Alexandra Motut, University of Toronto