| 【Aim】 |
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This course provides an introduction to speech signal processing and natural language processing. Topics include fundamentals and recent advances in the theory and practice of speech and language processing, such as hidden Markov models, automatic speech recognition, text-to-speech synthesis, speech coding, morphological analysis, syntactic analysis，and information retrieval.
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| 【Schedule】 |
- Spoken language and human interface
- Human speech production and speech analysis
- Parametric representation of speech signals
- Statistical modeling of speech using hidden Markov model (HMM)
- Speech recognition
- Speech synthesis
- Speech and audio coding, speech enhancement, and other applications
- Introduction to language processing
- Morphological analysis for Japanese: Word segmentation
- Morphological analysis for English: POS tagging
- Top-down/Bottom-up parsing
- Probabilistic Context Free Grammar
- Foundation of information retrieval
- Text mining
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| 【Texts, etc】 |
| Lecture notes will be handed out in class.
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| 【Prerequisite】 |
| Students are expected to have basic knowledge on discrete-time signal processing and probability theory.
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| 【How to Grade】 |
| Evaluation will be based on homework, midterm and final exams.
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| 【Message form the Lecturer】 |
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