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Course Detail

Course Name Speech Recognition and Understanding
Course Code 23AID476
Program B.Tech in Artificial Intelligence and Data Science
Credits 3
Campus Coimbatore , Amritapuri ,Faridabad , Bangaluru, Amaravati

Syllabus

Introduction of speech recognition – Overview of speech recognition systems – Speech recognition formulations – Feature extraction – Alignment – Hidden Markov Model – Advanced acoustic modelling – Language model – Deep learning for speech recognition – Advanced neural network architectures for acoustic model – End-to-end ASR

Objectives and Outcomes

Course Objectives

  • The main objective of the course is to give an introduction to recognition and understanding of the speech
  • This course introduces different approaches to build a speech recognition system
  • This course helps the students to understand language model and acoustic models required for building a speech recognition system
  • This courses introduces different deep learning architectures used for implementing the end to end automatic speech recognition system

Course Outcomes

After completing this course, students will be able to

CO1

Implement language and acoustic models required for a speech recognition system

CO2

Develop a feature extraction model for speech recognition

CO3

Implement a speech recognition model

CO4

Develop a deep learning based end to end speech recognition model

CO-PO Mapping

PO/PSO

PO1

PO2

PO3

PO4

PO5

PO6

PO7

PO8

PO9

PO10

PO11

PO12

PSO1

PSO2

PSO3

CO

CO1

2

2

2

2

2

–

–

1

–

–

–

2

3

1

1

CO2

2

2

2

2

2

–

–

1

–

–

–

2

3

1

1

CO3

2

2

2

2

2

–

–

1

–

–

–

2

3

1

1

CO4

2

2

2

2

2

–

–

1

–

–

–

2

3

1

1

Evaluation Pattern

Evaluation Pattern

Assessment

Internal/External

Weightage (%)

Assignments (minimum 2)

Internal

30

Quizzes (minimum 2)

Internal

20

Mid-Term Examination

Internal

20

Term Project/ End Semester Examination

External

30

23AID477 Social Media Text Analysis L-T-P-C: 2- 0- 2- 3

Text Books / References

Text Books / References

  1. R. Rabiner, B. H. Jhuang and B. Yegnanarayana, “Fundamentals of speech recognition”, Pearson Education, 2009.
  2. R. Deller, Jr., J. H. L. Hansen and J. G. Proakis Discrete-Time Processing of Speech Signals, Wiley-IEEE Press, NY, USA, 1999.
  3. O’Shaughnessy, Speech Communications: Human and Machine, Second Edition,University Press, 2005.
  4. Benesty, M. M. Sondhi and Y. Huang, “Handbook of speech processing”, Springer, 2008.

Daniel Jurafsky, James H Martin, Speech & language processing, preparation [cited 2020 June 1] Available from: https://web. stanford. edu/~ jurafsky/slp3 (2018).

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