Profile-ID : 60519



  • Prof Umesh Srinivasan

  • Professor
  • Indian Institute of Technology, Madras
Publications 1992 - 2019

Publications

  • 23
    Journal Articles
  • 82
    Conference Paper
  • 1
    Editorial
  • 57
  • 10

Citations / H-Index

655 Citations
15 h-index
251 Citations

Co-author Network


Expertise

Electrical and Electronic Engineering

Speaker Normalization and Adaptation, Speaker & Speech Recognition, Spectral Analysis, Detection & Estimation Theory, Digital Signal Processing

Personal Information

Prof Umesh Srinivasan

Male
Department of Electronics and Electrical Engineering, Indian Institute of Technology Madras, Tamil Nadu, India
India,Tamil Nadu,Chennai - 600036


Experience

  • Professor

    Indian Institute of Technology, Madras


Qualification

  • Ph.D

    University of Rhode Island


Doctoral Theses Guided

2018

Use of articulatory features and cross-lingual techniques in acoustic modeling of low-resource languages

Basil Abraham, Indian Institute of Technology Madras

2018

KNOWLEDGE TRANSFER USING dnns IN UN-SUPERVISED SPEAKER NORMALIZATION AND DYSARTHRIC SPEECH RECOGNITION

Neethu Mariam Joy, Indian Institute of Technology Madras

2011

Computationally efficient speaker identificaton and use of multiple background models for spaker verification .

Achintya kumar Sarkar, Indian Institute of Technology Madras

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2018

Use of articulatory features and cross-lingual techniques in acoustic modeling of low-resource languages

Basil Abraham, Indian Institute of Technology Madras

2018

KNOWLEDGE TRANSFER USING dnns IN UN-SUPERVISED SPEAKER NORMALIZATION AND DYSARTHRIC SPEECH RECOGNITION

Neethu Mariam Joy, Indian Institute of Technology Madras

2011

Computationally efficient speaker identificaton and use of multiple background models for spaker verification .

Achintya kumar Sarkar, Indian Institute of Technology Madras

2010

Computationally efficient vtln for class-specific frequency warping and rapid adaptation .

Shakti, Prasad Rath, Indian Institute of Technology Madras

Read Less