NOC:Digital Speech Processing

Lecture 1

Lecture 2

Lecture 3

Lecture 4

Lecture 5

Lecture 6

Lecture 7

Lecture 8

Lecture 9

Lecture 10

Lecture 11

Lecture 12

Lecture 13

Lecture 14

Lecture 15

Lecture 16 - Human Auditory System

Lecture 17

Lecture 18

Lecture 19 - Time Domain Methods in Speech Processing

Lecture 20

Lecture 21 - Introduction to Liner Prediction

Lecture 22 - Autocorrelation Method of LPC analysis

Lecture 23 - Autocorrelation Method of LPC analysis (Continued...)

Lecture 24 - Lattice Formulations of Linear Prediction

Lecture 25 - Lattice Formulations of Linear Prediction (Continued...)

Lecture 26

Lecture 27

Lecture 28

Lecture 29

Lecture 30

Lecture 31 - Segmental and Supra-segmental features of speech signal

Lecture 32 - Cepstral Transform Coefficients (CC) Parameters extraction

Lecture 33 - Mel Frequency Cepstral Coefficients

Lecture 34 - MFCC features vector

Lecture 35 - Fundamental Frequency (F0) Detection of speech signal

Lecture 36 - Frequency Domain Fundamental Frequency Detection Algorithms

Lecture 37 - Text to Speech Synthesis

Lecture 38 - Text to Speech Synthesis (Continued...)

Lecture 39 - Automatic Speech Recognition

Lecture 40 - Statistical Modeling of Automatic Speech Recognition

Lecture 41 - Speech based Technology Development for e-learning

Lecture 42 - Prosody Modeling

Lecture 43 - Fundamental frequency countur modeling

Lecture 44 - Fundamental frequency contour modeling (Continued...)