Multilingual Natural Language Processing

CMU CS 11737, Fall 2020

TBA

Graham Neubig (office hours: TBA), gneubig@cs.cmu.edu
Yulia Tsvetkov (office hours: TBA), ytsvetko@cs.cmu.edu
Alan W Black (office hours: TBA), awb@cs.cmu.edu

Teaching Assistants:
Cindy Wang (office hours: TBA), xinyiw1@cs.cmu.edu
Sachin Kumar (office hours: TBA), sachink@cs.cmu.edu
Tanmay Parekh (office hours: TBA), tparekh@cs.cmu.edu

Forum: Piazza

Learning Goals

Students who take this course should be able to develop linguistically motivated solutions to core and applied NLP tasks for any language. This includes understanding and mitigating the difficulties posed by lack of data in low-resourced languages or language varieties, and the necessity to model particular properties of the language of interest such as complex morphology or syntax. The course will introduce modeling solutions to these issues such as multilingual or cross-lingual methods, linguistically informed NLP models, and methods for effectively bootstrapping systems with limited data or human intervention. The project work will involve building an end-to-end NLP pipeline in a language you don’t know.


Pre-requisites

You must have taken an NLP class previously. Some examples include:

The assignments for the class will be done by creating neural network models, and examples will be provided using PyTorch. If you are not familiar with PyTorch, we suggest you attempt to familiarize yourself using online tutorials (for example “Deep Learning for NLP with PyTorch”) before starting the class.


Announcements


Syllabus

The lecture plan is subject to change.

Week Date Topics Readings Homeworks
1 Aug 31 Course Introduction [slides]  

Readings

To be updated


Grading

To be updated


Policies

Academic honesty. Homework assignments are to be completed individually. Verbal collaboration on homework assignments is acceptable, as well as re-implementation of relevant algorithms from research papers, but everything you turn in must be your own work, and you must note the names of anyone you collaborated with on each problem and cite resources that you used to learn about the problem. Suspected violations of academic integrity rules will be handled in accordance with the CMU guidelines on collaboration and cheating.


Note to Students

Take care of yourself! As a student, you may experience a range of challenges that can interfere with learning, such as strained relationships, increased anxiety, substance use, feeling down, difficulty concentrating and/or lack of motivation. All of us benefit from support during times of struggle. There are many helpful resources available on campus and an important part of having a healthy life is learning how to ask for help. Asking for support sooner rather than later is almost always helpful. CMU services are available, and treatment does work. You can learn more about confidential mental health services available on campus at: http://www.cmu.edu/counseling/. Support is always available (24/7) from Counseling and Psychological Services: 412-268-2922.

Accommodations for Students with Disabilities:

If you have a disability and have an accommodations letter from the Disability Resources office, I encourage you to discuss your accommodations and needs with me as early in the semester as possible. I will work with you to ensure that accommodations are provided as appropriate. If you suspect that you may have a disability and would benefit from accommodations but are not yet registered with the Office of Disability Resources, I encourage you to contact them at access@andrew.cmu.edu.