Introduction: speech production and perception, information sources in speech, linguistic aspect of speech, acoustic and articulatory phonetics, nature of speech ,models for speech analysis and perception; Short ‐ term processing: need, approach, time, frequency and time ‐ frequency analysis; Short ‐ term Fourier transform (STFT): overview of Fourier representation, non ‐ stationary signals, development of STFT, transform and filter ‐ bank views of STFT; cesptrum analysis: Basis and development, delta, delta ‐ delta and mel ‐ cepstrum, homomorphic signal processing, real and complex cepstrum; Linear Prediction (LP) analysis: Basis and development, Levinson‐Durbin’s method, normalized error, LP spectrum, LP cepstrum, LP residual; Sinusoidal analysis: Basis and development, phase unwrapping, sinusoidal analysis and synthesis of speech; Speech coding: Need and parameters, classification, waveform coders, speech ‐ specific coders, GSM, CDMA and other mobile coders; Applications: Some applications like pitch extraction, spectral analysis and coding standard.

Same as Reference

1. Digital Processing of Speech Signals Pearson Education, L.R..Rainer and R.W.Schafer, Delhi, India, 2004.

2. Discrete-Time Processing of Speech Signals, J.R.Deller, Jr., J.H.L.Hansen, and J.G.Proakis, Wiley‐IEEE Press, NY,USA, 1999.

3. Human and Machine, D.O’ Shaughnessy, Speech Communications: Second Edition, University Press, 2005.

4. Discrete-time processing of speech signals, T.F.Quatieri, Pearson Education, 2005.

5. Fundamentals of speech recognition, L.R.Rabiner, B.H. Jhuang and B.Yegnanarayana Pearson Education, 2009.

Course Outcomes (COs):

CO1: Understand the fundamentals of speech in signal processing

CO2: Analyse the time and frequency domain characteristics of speech through different transforms

CO3: Study the cesptrum analysis of signals

CO4: Understand the different methods in speech coding

CO5: Apply the speech processing in real time applications