Courses

Graduate Courses

Computational linguistics

  • CSCI 544: Applied Natural Language Processing

    Introduction to key components of human language technologies, including: parsing, discourse, dialogue, information extraction, sentiment analysis, question answering, analysis of linguistic structure.
    Instructors: Core and Georgila (Fall), and Artstein (Spring).

  • CSCI 662: Advanced Natural Language Processing

    Computational models of natural language. Formalisms for describing structures of human language, and algorithms for learning language structures from data.
    Instructor: Knight.

  • CSCI 699: Introduction to Information Extraction

    Introduce and discuss many of the sub-problems and methods of information extraction, including use of textual patterns, language and formatting features, generative and conditional models, rule-learning and deep learning techniques. Will discuss segmentation of text streams, classification of segments into fields, association of fields into records, and clustering and de-duplication of records.
    Instructor: Xiang

  • CSCI 599: Machine Translation

    Introduction to machine translation, with a focus on statistical approaches. Word-based, phrase-based, and syntax-based translation; current research questions in machine translation.
    Instructors: Chiang and Knight. Last offered Spring 2014.

  • CSCI 599: Information Retrieval

    Fundamental topics in Information Retrieval, the science of searching for and making sense of information from large collections of text.
    Instructor: Leuski.
    Last offered Spring 2012.

  • CSCI 599: Human Communication and Machine Learning

    Machine learning, pattern recognition, and signal processing tools to analyze, recognize, and predict human communication behaviors during social interactions.
    Instructors: Morency and Scherer.
    Last offered Fall 2012.

  • CSCI 599: Natural Language Dialogue Systems

    Computational techniques and active research areas in natural language dialogue systems. Spoken language understanding, modeling dialogue genres, dialogue management and representing context, dialogue response policies, natural language generation, embodied conversational agents, incremental speech processing, and dialogue system evaluation.
    Instructors: DeVault and Traum.
    Last offered Spring 2013.

  • EE 519: Speech Recognition and Processing for Multimedia

    Speech production, acoustics, perception, synthesis, compression, recognition, transmission. Coding for speech, music, and CD-quality. Feature extraction. Echo cancellation. Audio, visual synchronization. Multimedia, Internet use.
    Instructor: Narayanan.

  • EE 619: Advanced Topics in Automatic Speech Recognition

    Modern automatic speech recognition systems, with emphasis on statistical methods and modeling techniques. Hidden Markov models (HMMs), acoustic modeling using HMMs, front end processing for robustness, statistical language models, and dialogue modeling.
    Instructor: Narayanan.

Related fields

  • CSCI 561: Introduction to Artificial Intelligence
  • CSCI 573: Advanced Artificial Intelligence
  • CSCI 567: Machine Learning
  • EE 517: Statistics for Engineers
  • EE 559: Mathematical Pattern Recognition
  • EE 565: Information Theory
  • LING 531: Phonology
  • LING 547: Morphology
  • LING 530: Generative Syntax
  • LING 537: Advanced Syntax
  • LING 534: Logic and the Theory of Meaning
  • LING 576: Psycholinguistics
  • MATH 505: Applied Probability
  • MATH 511: Data Analysis
  • MATH 541: Introduction to Mathematical Statistics
  • MATH 547: Methods of Statistical Inference

Undergraduate Courses

  • LING 285Lg: Human Language and Technology

    Study of human linguistic competence and technologies that simulate it. Grammar, parsing, text generation; semantics, pragmatics, sense disambiguation; phonetics, speech synthesis, speech recognition. Instructor: Iskarous.