Course11710514544 lectures
Digital Speech Processing
Prof. Shyamal Kumar Das Mandal · IIT Kharagpur
About
Oral Speech may be the most natural, common and direct mode of human communication. Since the middle of the last century, Speech has become an area of intense and active research and development (R&D) to become a prime means of direct Human-Computer Interactions (HCI). The pace of such R&D has farther got boosted with the general abundance of cheap computing power in the form of PC, PDA or Mobile Handset. While man to machine in speech mode is yet to reach the minimum threshold level for wide-spread deployment, spoken messages directly by machine. This need research in speech science and development of speech technology. The course provides the foundation knowledge on speech production and perception along with processing of speech signal in digital domain.
Intended audience: ECE, CS, EE, IE
Prerequisites: Digital Signal Processing or Signals and System
Lectures
Week 1
- 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
Week 2
- 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
Week 3
- 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)
week 4
- 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.)
Week 5
- 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
Week 6
- 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
Week 7
- 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
Week 8
Syllabus and materials
At NPTEL, as the course publishes them.
Credits and licence
- Institution
- IIT Kharagpur
- Department
- Electrical Engineering
- Teacher
- Prof. Shyamal Kumar Das Mandal
- Level
- Undergraduate
- Language
- English
- Subjects
- Engineering
- Source
- NPTEL
- Licence
- CC BY-NC-SA, as NPTEL states it. Non-commercial use only. NPTEL's terms
- Attribution
- NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge.
- Who can watch
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