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MD3005 SPEECH PROCESSING SYLLABUS | ANNA UNIVERSITY BE MEDICAL ELECTRONICS ENGINEERING 6TH SEMESTER SYLLABUS REGULATION 2008 2011 2012-2013

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MD3005 SPEECH PROCESSING SYLLABUS | ANNA UNIVERSITY BE MEDICAL ELECTRONICS ENGINEERING 6TH SEMESTER SYLLABUS REGULATION 2008 2011 2012-2013 BELOW IS THE ANNA UNIVERSITY SIXTH SEMESTER B.E MEDICAL ELECTRONICS ENGINEERING DEPARTMENT SYLLABUS, TEXTBOOKS, REFERENCE BOOKS,EXAM PORTIONS,QUESTION BANK,PREVIOUS YEAR QUESTION PAPERS,MODEL QUESTION PAPERS, CLASS NOTES, IMPORTANT 2 MARKS, 8 MARKS, 16 MARKS TOPICS. IT IS APPLICABLE FOR ALL STUDENTS ADMITTED IN THE YEAR 2011 2012-2013 (ANNA UNIVERSITY CHENNAI,TRICHY,MADURAI, TIRUNELVELI,COIMBATORE), 2008 REGULATION OF ANNA UNIVERSITY CHENNAI AND STUDENTS ADMITTED IN ANNA UNIVERSITY CHENNAI DURING 2009

MD3005 SPEECH PROCESSING L T P C
3 0 0 3
UNIT I ANALYTICAL BACKGROUND AND TECHNIQUES 9
Analysis of Discrete – Time speech signals – Time frequency analysis of speech-
Analysis based on Linear predictive loading- Cepstral Analysis of Speech- Automatic
Extraction and Tracking of Speech Formants- Automatic extraction of voicing pitch-
Auditory Model for speech Analysis-
Linear Model and Dynamic System Model-Linear Model- Time-Varying Linear Model-
Linear Dynamic System Model- Time-Varying Linear Dynamic Systems Model-
Nonlinear Dynamic System Model
UNIT II FUNDAMENTALS OF SPEECH SCIENCE 9
Phonetic Process – Introduction- Articulatory Phonetics and Speech generation-
Acoustic Models of Speech Production- Coarticulation- Acoustic – Phonetics and
characterization of speech signals- Introduction to Auditory Phonetics- Sound
Perception- Speech Perception Phonological process – phonemes- Features-
Articulatory Phonology
UNIT III MODELS FOR AUDITORY SPEECH PROCESSING 9
Models for the Cochlear function- Frequency Domain Solution of the Cochlear Model-
Time Domain Solution of the Cochlear Model- Stability Analysis for Time Domain
Solution of the Cochlear Model- Models for inner hair cells and for synapses to Authority
nerve fibres- Interval based speech feature extraction from the cochlear model outputs-
Interval-Histogram representation for the speech sound in Quiet in noise- models for
network structures in the auditory pathway.
63
UNIT IV SPEECH CODING 9
Introduction- Statistical Models- Scalar Quantization- Vector Quantization (VQ)-
Frequency-Domain Coding- Model–Based Coding- LPC Residual Coding
UNIT V SPEECH TECHNOLOGY IN SELECTED AREAS 9
Speech Recognition – Introduction- Mathematical formulation- Acoustic Pre-processor-
Use of HMMs in Acoustic Modelling- Use of higher order statistical models in acoustic
modelling- case study – speech recognition using a Hidden Markov Model - Robustness
of Acoustic Modelling and Recognizer Design- Speed synthesis – Introduction- Basic
approaches- Synthesis Methods- Databases- Case Study – Automatic unit selection for
waveform speech synthesis
TOTAL: 45 PERIODS
REFERENCES:
1. Li Deng Douglas O’Shaughnessy- “Speech Processing: A Dynamic and Optimization
oriented Approach”- Signal Processing and Communication Series- Printed in USA-
2003
2. Thomas F-Quatieri- “Discrete Time Speech Signal Processing: Principles and
Practice”- Pearson Education- New Delhi- 2006
3. Rabiner and Schaffer Pearson
4. John R., Jr. Deller , Discrete-Time Processing of Speech Signals , Wiley-IEEE
Press-1999
5. Quatieri, Discrete-Time Speech Signal Processing: Principles and Practice,PHI-2006

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