Speech and Language Processing

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Kobayashi Takao  Okumura Manabu 
Lecture2  Exercise0  Experiment0
Syllabus updated
Lecture notes updated
Fall Semester

Outline of lecture

The lecture covers the fundamentals of speech signal processing and natural language processing. The topics includes hidden Markov models, automatic speech recognition, text-to-speech synthesis, speech coding, morphological analysis, syntactic analysisシ径nd information retrieval. Students will be able to learn basic and advanced techniques of doing speech and language processing using computer.

Purpose of lecture

To provide an introduction to speech signal processing and natural language processing. Also to provide not only fundamentals but also recent advances in the theory and practice of spoken language and natural language processing systems.

Plan of lecture

1. Spoken language and human interface
2. Human speech production and speech analysis
3. Parametric representation of speech signals
4. Statistical modeling of speech using hidden Markov model (HMM)
5. Speech recognition
6. Speech synthesis
7. Speech coding, speech enhancement, and other applications
8. Introduction to language processing
9. Morphological analysis for Japanese: Word segmentation
10. Morphological analysis for English: POS tagging
11. Top-down/Bottom-up parsing
12. Probabilistic Context Free Grammar
13. Foundation of information retrieval
14. Text mining

Textbook and reference

Lecture notes will be handed out in class.

Related and/or prerequisite courses

Students are expected to have basic knowledge on discrete-time signal processing and probability theory.


Evaluation will be based on homework and final exam.

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