DS7301 SPEECH AND AUDIO SIGNAL PROCESSING SYLLABUS FOR ME ECE 3RD SEMESTER - Anna University Internal marks 2018

DS7301 SPEECH AND AUDIO SIGNAL PROCESSING SYLLABUS FOR ME ECE 3RD SEMESTER

 ANNA UNIVERSITY, CHENNAI
REGULATIONS - 2013
DS7301 SPEECH AND AUDIO SIGNAL PROCESSING SYLLABUS
ME 3RD SEM ELECTRONICS AND COMMUNICATION ENGINEERING SYLLABUS
DS7301 SPEECH AND AUDIO SIGNAL PROCESSING SYLLABUS
DS7301 SPEECH AND AUDIO SIGNAL PROCESSING SYLLABUS
OBJECTIVES:
1. To study the basic concepts of speech and audio.
2. To study the analysis of various M-band filter banks for audio coding
3. To learn various transform coders for audio coding.
4. To study the speech processing methods in time and frequency domain
 
UNIT I MECHANICS OF SPEECH AND AUDIO
Introduction - Review Of Signal Processing Theory-Speech production mechanism – Nature of Speech signal – Discrete time modelling of Speech production – Classification of Speech sounds – Phones – Phonemes – Phonetic and Phonemic alphabets – Articulatory features. Absolute Threshold of Hearing - Critical Bands- Simultaneous Masking, Masking-Asymmetry, and the Spread of Masking- Non simultaneous Masking - Perceptual Entropy - Basic measuring philosophy -Subjective versus objective perceptual testing - The perceptual audio quality measure (PAQM) - Cognitive effects in judging audio quality.

UNIT II TIME-FREQUENCY ANALYSIS: FILTER BANKS AND TRANSFORMS
Introduction -Analysis-Synthesis Framework for M-band Filter Banks- Filter Banks for Audio Coding: Design Considerations - Quadrature Mirror and Conjugate Quadrature Filters- Tree- Structured QMF and CQF M-band Banks - Cosine Modulated “Pseudo QMF” M-band Banks - Cosine Modulated Perfect Reconstruction (PR) M-band Banks and the Modified Discrete Cosine Transform (MDCT) - Discrete Fourier and Discrete Cosine Transform - Pre-echo Distortion- Preecho Control Strategies.

UNIT III AUDIO CODING AND TRANSFORM CODERS
Lossless Audio Coding-Lossy Audio Coding- ISO-MPEG-1A,2A,2A Advanced, 4Audio Coding - Optimum Coding in the Frequency Domain - Perceptual Transform Coder -Brandenburg-Johnston Hybrid Coder - CNET Coders - Adaptive Spectral Entropy Coding -Differential Perceptual Audio Coder - DFT Noise Substitution -DCT with Vector Quantization -MDCT with Vector Quantization.

UNIT IV TIME AND FREQUENCY DOMAIN METHODS FOR SPEECH PROCESSING

Time domain parameters of Speech signal – Methods for extracting the parameters :Energy, Average Magnitude – Zero crossing Rate – Silence Discrimination using ZCR and energy Short Time Fourier analysis – Formant extraction – Pitch Extraction using time and frequency domain methods 
HOMOMORPHIC SPEECH ANALYSIS:
Cepstral analysis of Speech – Formant and Pitch Estimation – Homomorphic Vocoders. 
 
UNIT V LINEAR PREDICTIVE ANALYSIS OF SPEECH
Formulation of Linear Prediction problem in Time Domain – Basic Principle – Auto correlation method – Covariance method – Solution of LPC equations – Cholesky method – Durbin’s Recursive algorithm – lattice formation and solutions – Comparison of different  methods – Application of LPC parameters – Pitch detection using LPC parameters – Formant analysis – VELP – CELP.

TOTAL: 45 PERIODS

REFERENCES:

1. Digital Audio Signal Processing, Second Edition, Udo Zölzer, A John Wiley& sons Ltd Publicatioons
2. Applications of Digital Signal Processing to Audio And Acoustics Mark Kahrs, Karlheinz Brandenburg, Kluwer Academic Publishers New York, Boston, Dordrecht, London, Moscow.
3. Digital Processing of Speech signals – L. R. Rabiner and R.W. Schaffer - Prentice Hall - 1978

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