| Time | 1:00 to 1:50 PM | |
| Place | 250 Simrall | |
| Instructor |
Joseph Picone Office: 2133 CAVS Office Hours: 8-9 MWF (others by appt.) Email: picone@ece.msstate.edu |
|
| Class Alias | ece_8463@cavs.msstate.edu | |
| URL | http://www.cavs.msstate.edu/research/isip/publications/courses/ece_8463 | |
| Required Textbook(s) | X. Huang, A. Acero, and H.W. Hon, Spoken Language Processing - A Guide to Theory, Algorithm, and System Development, Prentice Hall, ISBN: 0-13-022616-5, 2001. | |
| Prerequisite | S.J. Orfandis, Introduction to Signal Processing, Prentice-Hall, ISBN: 0-13-209172-0, 1996. | |
| Reference Textbook(s) |
F. Jelinek,
Statistical Methods for Speech Recognition,
MIT Press, ISBN: 0-262-10066-5, 1998.
J. Deller, et. al., Discrete-Time Processing of Speech Signals, MacMillan Publishing Co., ISBN: 0-7803-5386-2, 2000. S. Pinker, The Language Instinct: How the Mind Creates Language, Harperperennial Library, ISBN: 0-0609-5833-2, 2000. D. Jurafsky and J.H. Martin, SPEECH and LANGUAGE PROCESSING: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition, Prentice-Hall, ISBN: 0-13-095069-6, 2000. S. Furui, Digital Speech Processing, Synthesis, and Recognition, Marcel Dekker, ISBN: 0-8247-0452-5, 2000. D. O'Shaughnessy, Speech Communications: Human and Machine, IEEE Press, ISBN: 0-7803-3449-3, 2000. L.R. Rabiner and B.W. Juang, Fundamentals of Speech Recognition, Prentice-Hall, ISBN: 0-13-015157-2, 1993. L.R. Rabiner and R.W. Schafer, Digital Processing of Speech Signals, Prentice-Hall, ISBN: 0-13-213603-1, 1978. |
| Exam No. 1 | 25% |
| Exam No. 2 | 25% |
| Exam No. 3 | 25% |
| Final Exam (Cumulative) | 25% |
| Class | Date | Section(s) | Topic(s) | |
| 01 | 08/18 | 1.1 - 1.5 | Course Overview; Introduction | |
| 02 | 08/20 | 2.1.2 | Speech Physiology | |
| 03 | 08/23 | 6.2 | Speech Production Models | |
| 04 | 08/25 | 2.1.3, 2.1.4 | Hearing Physiology | |
| 05 | 08/27 | 2.1.3.4 | Perception and Masking | |
| 06 | 08/30 | 2.2 | Phonetics and Phonology | |
| 07 | 09/01 | 2.3 - 2.5 | Syntax and Semantics | |
| 08 | 09/03 | 5.5, 9.3 | Sampling | |
| 09 | 09/08 | 5.6, 5.7 | Resampling | |
| 10 | 09/10 | 10.1 - 10.4 | Acoustic Transducers | |
| 11 | 09/13 | 5.4 | Temporal Analysis | |
| 12 | 09/15 | 5.1 - 5.3 | Frequency Domain Analysis | |
| 13 | 09/17 | Lectures 1-11 | Exam No. 1 | |
| 14 | 09/20 | 6.4 - 6.5 | Cepstral Analysis | |
| 15 | 09/22 | 6.1 - 6.3 | Linear Prediction | |
| 16 | 09/24 | 6.5.3 | LP-Based Representations | |
| 17 | 09/27 | 6.5.3, 9.3.4 | Spectral Normalization | |
| 18 | 09/29 | 9.3.3 | Differentiation | |
| 19 | 10/01 | 9.3.4, 3.2.2 | Principal Components | |
| 10/04 | 02/22 | 9.3.4, 3.2.2 | Linear Discriminant Analysis | |
| 21 | 10/06 | 8.2.1 | Dynamic Programming | |
| 22 | 10/08 | 8.2.2, 8.2.3 | Fundamentals of Markov Models | |
| 23 | 10/11 | 8.2.4, 4.4.2 | Parameter Estimation | |
| 24 | 10/13 | 8.2.4 | HMM Training | |
| 25 | 10/15 | 4.4.3, 8.3 | Continuous Mixture Densities | |
| 26 | 10/20 | 8.4 | Practical Issues | |
| 27 | 10/22 | 4.5 | Decision Trees | |
| 28 | 10/25 | Lectures 12 - 28 | Exam No. 2 | |
| 29 | 10/27 | 8.5 | Limitations of HMMs | |
| 30 | 10/29 | 11.1 | Formal Language Theory | |
| 31 | 11/01 | 11.2.1 | Context Free Grammars | |
| 32 | 11/03 | 11.2.2, 11.3 | N-gram Models and Complexity | |
| 33 | 11/05 | 11.4 | Smoothing | |
| 34 | 11/08 | 12.1 | Basic Search Algorithms | |
| 35 | 11/10 | 12.2 - 12.4 | Time Synchronous Search | |
| 36 | 11/12 | 12.5 - 13.6 | Stack Decoding | |
| 37 | 11/15 | 13.1.1 - 13.1.3 | Lexical Trees | |
| 38 | 11/17 | 13.1.4 - 13.1.6 | Efficent Trees | |
| 39 | 11/19 | 3.2.3, 9.6 | Adaptation | |
| 40 | 11/22 | Lectures 29 - 37 | Exam No. 3 | |
| 41 | 11/29 | 4.3 | Discriminative Training | |
| 42 | 12/01 | 4.3.3, 9.8.1 | Neural Networks | |
| 43 | 12/03 | N/A | Evaluation Metrics and Common Evaluations | |
| 46 | 12/07 | Cumulative | Final Exam (12 - 3 PM) |
| No. | Due Date | Description |
| 1 | 08/30 | Speech Production |
| 2 | 09/08 | Speech Perception |
| 3 | 09/13 | Linguistics |
| 4 | 09/20 | Sampling |
| 5 | 09/27 | Frequency Response |
| 6 | 10/04 | Linear Prediction and the Cepstrum |
| 7 | 10/11 | Principle Components Analysis |
| 8 | 10/20 | Differentiation |
| 9 | 10/25 | Dynamic Programming |
| 10 | 11/01 | HMM Training |
| 11 | 11/08 | EM Estimation |
| 12 | 11/15 | N-grams |
| 13 | 11/22 | Smoothing |
| 14 | 11/29 | Search |