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Degree Level Course

Speech Technology

Code BSEE4001
Credits 4 Credits
Type Elective
Prerequisites None
Core Competencies

What You'll Learn

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  • To understand the concepts of speech and speech technologies, and to apply them to real-world scenarios

  • To gain hands-on experience of the relevant toolkits used for speech processing

12-Week Roadmap

Course Structure & Syllabus

For details of standard term assessment timelines and exam structures, visit our Academics page.

WEEK 1
Review of Signals and Systems, Continuous time signals and transforms Discrete time signals, Discrete Fourier transform, Autocorrelation and Cross-Correlation
WEEK 2
Acoustic Feature Analysis of Speech Signals I, II Gaussian mixture models (GMM), universal background model (UBM-GMM), singular value decomposition (SVD)
WEEK 3
Hidden Markov model (HMM), Examples of HMM based approach for ASR, TTS, speaker diarization Information bottleneck (IB) based clustering for diarization
WEEK 4
Introduction and History of ASR and TTS Components of ASR: Acoustic Modelling, Punctuation Model (Lexicon) and language modelling (N-Gram Language models)
Reading List

Prescribed Books & References

  • L R Rabiner and R W Schafer, "Theory and Application of Digital Speech Processing", PH, Pearson, 2011.
  • L R Rabiner, B-H Juang and B Yegnanarayana, "Fundamentals of Speech Recognition", Pearson, 2009 (Indian subcontinent adaptation).
  • Xuedong Huang, Alex Acero, Hsiao-wuen Hon, "Spoken Language Processing: A guide to Theory, Algorithm, and System Development", Prentice Hall PTR, 2001.
  • References:
  • Thomas Quatieri, "Discrete-time Speech Processing: Principles and Practice", PH, 2001.
  • Rabiner and Schafer, "Digital Processing of Speech Signals", Pearson Education, 1993.
  • Recent research papers
Faculty & Experts

About the Instructors

Prof. S. Umesh

Prof. S. Umesh

Professor , Department of Electrical Engineering, Indian Institute of Technology , IIT Madras

S. Umesh is a  Professor of Electrical Engineering at IIT-Madras. He completed his PhD from the University of Rhode Island,USA and his PostDoctoral Fellowship from the City University of New York. He has also been a visiting researcher at AT&T Research Laboratories, USA; at Machine Intelligence Laboratory Cambridge University Engineering Department, UK and the Department of Computer Science, RWTH-Aachen, Germany.

He is a recipient of the AICTE Career Award for Young Teachers in 1997 and the Alexander von Humboldt Research Fellowship in 2004.  During his stint at Cambridge University in 2004, he was part of the U.S. DARPA's Effective, Affordable Reusable Speech-to-text (EARS) programme. Similarly in 2005 he was part of the RWTH-Aachen's TC-STAR project for transcription of speech from European Parliament's Plenary Sessions. Between 2010-2016, he led a multi-institution consortium to develop ASR systems in Indian languages in the agriculture domain which was funded by MeiTY. He is currently leading the ASR efforts for the Natural Language Translation Mission managed by the Office of Principal Scientific Adviser of Govt. of India.

Other Courses by Instructor:
Prof. Hema A Murthy

Prof. Hema A Murthy

Professor , Department of Computer Science and Engineering , IIT Madras

Faculty at the Department of Computer Science and Engineering, Indian Institute of Technology Madras.