Describe, compare, and apply the main theories used in corpus linguistics, using qualitative and quantitative corpora, to perform diachronic and synchronic analyses. Restricted to students in the M.D.S. program with Computational Linguistics option. This course is not eligible for Credit/D/Fail grading.
Advanced computational techniques in multilingual corpora. Language change and linguistic variation; best practices for data collection, annotation and analysis. Restricted to students in the M.D.S. program with Computational Linguistics option. Prerequisite: All of DSCI 511, COLX 521. This course is not eligible for Credit/D/Fail grading.
Identify and differentiate morphological processes occurring in natural language for implementation in computational linguistics applications. Restricted to students in the M.D.S. program with Computational Linguistics option. This course is not eligible for Credit/D/Fail grading.
Morphological parsing tools to analyze and understand multiple languages, including majority and low-resource languages, and to demonstrate computational implementation of fragments. Restricted to students in the M.D.S. program with Computational Linguistics option. Prerequisite: COLX 525. This course is not eligible for Credit/D/Fail grading.
Machine translation (MT), including an ability to implement lexical translation models, discriminative training models, and syntactic models in MT. Includes noisy channel translation, phrase-based machine translation, and how to evaluate models. Restricted to students in the M.D.S. program with Computational Linguistics option. Prerequisite: DSCI 571. This course is not eligible for Credit/D/Fail grading.
Machine translation (MT) for diverse groups of languages. Tools covered will include syntax decoding, synchronous parsing, large-scale language modelling, system combination, morphology in MT, topics in modelling, example-based MT, mining parallel data, and quality estimation. Restricted to students in the M.D.S. program with Computational Linguistics option. Prerequisite: COLX 531. This course is not eligible for Credit/D/Fail grading.
Methods of natural language parsing: finite state approaches, class-based language models, part-of-speech tagging, NP chunking, shallow parsing, and context free syntactic parsing. Restricted to students in the M.D.S. program with Computational Linguistics option. Prerequisite: All of DSCI 511, DSCI 551, COLX 521. This course is not eligible for Credit/D/Fail grading.
Language processing to analyze lexical semantics. WordNet, FrameNet, and the semantic web, applied to word-sense disambiguation, entailment, question-answering, and knowledge base populations. Restricted to students in the M.D.S. program with Computational Linguistics option. Prerequisite: COLX 535. This course is not eligible for Credit/D/Fail grading.
Statistical and neural approaches to natural-language meaning in computational semantics. Restricted to students in the M.D.S. program with Computational Linguistics option. Prerequisite: COLX 561. This course is not eligible for Credit/D/Fail grading.
Data crawling, annotation, evaluation, and modelling lexical information. Restricted to students in the M.D.S. program with Computational Linguistics option. Prerequisite: COLX 563. This course is not eligible for Credit/D/Fail grading.
Computational tools in relation to low-resource and other under-documented and very-low-resource language. Restricted to students in the M.D.S. program with Computational Linguistics option. Prerequisite: COLX 535. This course is not eligible for Credit/D/Fail grading.
Techniques for identifying, analyzing, and synthesizing primary sources for the most current research in computational linguistics. Restricted to students in the M.D.S. program with Computational Linguistics option. This course is not eligible for Credit/D/Fail grading.
Techniques for identifying, analyzing, and synthesizing primary sources for the most current research in computational linguistics. Restricted to students in the M.D.S. program with Computational Linguistics option. Prerequisite: 24 credits of DSCI and COLX courses. This course is not eligible for Credit/D/Fail grading.