Course detail
Modern Methods of Speech Processing
FIT-MZDAcad. year: 2010/2011
Not applicable.
Language of instruction
Czech, English
Mode of study
Not applicable.
Guarantor
Learning outcomes of the course unit
Not applicable.
Prerequisites
Not applicable.
Co-requisites
Not applicable.
Planned learning activities and teaching methods
Not applicable.
Assesment methods and criteria linked to learning outcomes
Not applicable.
Course curriculum
Not applicable.
Work placements
Not applicable.
Aims
Not applicable.
Specification of controlled education, way of implementation and compensation for absences
Not applicable.
Recommended optional programme components
Not applicable.
Prerequisites and corequisites
Not applicable.
Basic literature
Psutka, J.: Komunikace s s počítačem mluvenou řečí. Academia, Praha, 1995
Gold, B., Morgan, N.: Speech and audio signal processing, John Wiley & Sons, 2000
Texty z http://www.fit.vutbr.cz/~cernocky/speech/
Recommended reading
Moore, B.C.J., : An introduction to the psychology of hearing, Academic Press, 1989
Jelinek, F.: Statistical Methods for Speech Recognition, MIT Press, 1998
Fukunaga, K.: Introduction to Statistical Pattern Recognition, Academic Press, 1990
Vapnik, V. N.:
Statistical Learning Theory,
Wiley-Interscience, 1998
Dutoit, T.: An Introduction to Text-To-Speech Synthesis, Kluwer Academic Publishers, 1997
Classification of course in study plans
Type of course unit
Lecture
39 hod., optionally
Teacher / Lecturer
Syllabus
- Review of notions: signal vectors and parameter matrices, basic statistics.
- Stochastic modeling of parameters, modeling of time by state sequences.
- Hidden Markov models: basic structure, training.
- Recognition of speech using HMM: Viterbi search, token passing.
- Pronunciation dictionaries and language models.
- Speech production and derived parameters: LPC, Log area ratios, line spectral pairs.
- Speech perception and derived parameters: Mel-frequency cepstral coefficients, Perceptual linear prediction.
- Temporal properties of hearing - RASTA filtering.
- Training the feature extractor on the data - linear discriminant analysis.
- Speech databases: standards, contents, speakers, annotations.
- Vocoders and modeling of the excitation: multi-pulse and stochastic excitations (GSM coding).
- CELP coding: long-term predictor, codebooks. Very low bit-rate coders.
- Current methods of speaker identification and verification.