CS 224S: Spoken Language Processing
Introduction to spoken language technology with an emphasis on dialogue and conversational systems. Automatic speech recognition, extraction of affect and social meaning from speech, speech synthesis, dialogue management, and applications to digital assistants, search, and recommender systems. Prerequisites:
CS 124, 221, 224N, or 229.
Terms: not given this year
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Units: 2-4
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Grading: Letter or Credit/No Credit
CS 224U: Natural Language Understanding (LINGUIST 188, LINGUIST 288)
Project-oriented class focused on developing systems and algorithms for robust machine understanding of human language. Draws on theoretical concepts from linguistics, natural language processing, and machine learning. Topics include lexical semantics, distributed representations of meaning, relation extraction, semantic parsing, sentiment analysis, and dialogue agents, with special lectures on developing projects, presenting research results, and making connections with industry. Prerequisites: one of
LINGUIST 180,
CS 124,
CS 224N,
CS224S, or
CS221; and logical/semantics such as
LINGUIST 130A or B,
CS 157, or
PHIL150
Terms: Spr
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Units: 3-4
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Grading: Letter or Credit/No Credit
LINGUIST 188: Natural Language Understanding (CS 224U, LINGUIST 288)
Project-oriented class focused on developing systems and algorithms for robust machine understanding of human language. Draws on theoretical concepts from linguistics, natural language processing, and machine learning. Topics include lexical semantics, distributed representations of meaning, relation extraction, semantic parsing, sentiment analysis, and dialogue agents, with special lectures on developing projects, presenting research results, and making connections with industry. Prerequisites: one of
LINGUIST 180,
CS 124,
CS 224N,
CS224S, or
CS221; and logical/semantics such as
LINGUIST 130A or B,
CS 157, or
PHIL150
Terms: Spr
|
Units: 3-4
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Grading: Letter or Credit/No Credit
LINGUIST 288: Natural Language Understanding (CS 224U, LINGUIST 188)
Project-oriented class focused on developing systems and algorithms for robust machine understanding of human language. Draws on theoretical concepts from linguistics, natural language processing, and machine learning. Topics include lexical semantics, distributed representations of meaning, relation extraction, semantic parsing, sentiment analysis, and dialogue agents, with special lectures on developing projects, presenting research results, and making connections with industry. Prerequisites: one of
LINGUIST 180,
CS 124,
CS 224N,
CS224S, or
CS221; and logical/semantics such as
LINGUIST 130A or B,
CS 157, or
PHIL150
Terms: Spr
|
Units: 3-4
|
Grading: Letter or Credit/No Credit
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