EFFECTIVE TRAINING OF RNN TRANSDUCER MODELS ON DIVERSE SOURCES OF SPEECH AND TEXT DATA
- ICASSP 2023
Samuel Thomas received his B.Tech degree in Computer Engineering from the Cochin University of Science and Technology, India and M.S degree in Computer Science and Engineering from the Indian Institute of Technology Madras, India before earning his Doctor of Philosophy degree from the Johns Hopkins University, Baltimore. Since graduation, he has been at the IBM T.J. Watson Research Center, New York with the Speech Technologies Group. In the past, he has worked on several speech research projects and workshops with the Center for Language and Speech Processing (CLSP) at JHU, the Idiap Research Institute, Switzerland and the TeNeT group, IIT Madras. His research interests include speech processing and machine learning for speech recognition, spoken language understanding, speech synthesis and speaker recognition. Samuel is a Senior Member of the IEEE and also an Associate Editor of the IEEE/ACM Transactions on Audio, Speech, and Language Processing.