Learn · Digital Speech Processing
Lecture 13 of 44Week 2
Lecture 13: Uniform Tube Modeling -V
Prof. Shyamal Kumar Das Mandal · IIT Kharagpur
Credits and licence
- From
- Digital Speech Processing, IIT Kharagpur (at NPTEL)
- Licence
- CC BY-NC-SA, as NPTEL states it. Non-commercial use only.
- Attribution
- NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge.
- Who can watch
- Tweens profiles and older. How courses are placed
All the lectures
- Lecture 1: Introducation to Digital Speech Processing
- Lecture 2 : Digitization and Recording
- Lecture 3 : Review of Digital Signal Processing Concepts
- Lecture 4 : Review of Digital Signal Processing Concepts (Contd.)
- Lecture 5 : Human Speech Production
- Lecture 6 : Place And Manner of Articulation
- Lecture 7 : Articulatory and Acoustic Phonetics
- Lecture 8 : Handson on Acoustic Phonetics
- Lecture 9 : Uniform Tube Modeling -I
- Lecture 10: Uniform Tube Modeling -II
- Lecture 11: Uniform Tube Modeling -III
- Lecture 12: Uniform Tube Modeling -IV
- Lecture 13: Uniform Tube Modeling -V
- Lecture 14: Uniform Tube Modeling -VI
- Lecture 15: Uniform Tube Modeling -VII
- Lecture 16: Speech Perception Part I
- Lecture 17: Speech Perception Part II
- Lecture 18: Speech Perception Part III
- Lecture 19: Time Domain Methods in Speech Processing
- Lecture 20:Time Domain Methods in Speech Processing (Continued)
- Lecture 21 : Introduction to Linear Prediction
- Lecture 22 : Autocorrelation Method of LPC analysis
- Lecture 23 : Autocorrelation Method of LPC analysis ( Contd.)
- Lecture 24 : Lattice Formulations of Linear Prediction
- Lecture 25 : Lattice Formulations of Linear Prediction ( Contd.)
- Lecture 26 : Overview of Short - Time Fourier Transform (STFT)
- Lecture 27 : Short-Time Fourier Transform Analysis
- Lecture 28 : Short-Time Fourier Transform Synthesis
- Lecture 29 : FBS and OLA
- Lecture 30 : Time-Frequency Sampling requirement of STFT synthesis
- 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 ( Contd.)
- 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 countur modeling (Contd.)