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，and information retrieval. Students will be able to learn basic and advanced techniques of doing speech and language processing using computer.
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.
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
Lecture notes will be handed out in class.
Students are expected to have basic knowledge on discrete-time signal processing and probability theory.
Evaluation will be based on homework and final exam.