Topic:

Machine Learning Basics – III

Abstract:

The talk would review the different types of classification methods and then look into a few static and dynamic methods with some examples. The static methods part [VQ, GMM] will be brief and the later part on dynamic methods namely DTW and HMM, using speaker identification and Speech recognition as applications to highlight the basics would be elaborate.

Bio of the Speaker:

Amitav Das got his PhD in Computer & Systems Engineering from University of California – Santa Barbara, his MS in Computer Engineering from RPI, New York and his B.Tech in Electronics & Telecom eng. from Jadavpur University. Amitav is one of those “returned-Indians”, who came back to India in 1999 after 15 years in the US and enjoying every moments of last 7 years stay in Bangalore. Amitav had a rich experience in developing products conducting core research as well as managing teams in various leading MNCs such as Philips Research Panasonic Research, Qualcomm, Motorola, and Siemens Research and now at Microsoft Research, India. During his 20 years plus career span in signal processing, he had contributed towards many products particularly in the wireless space as well as a few standards in international standard bodies such as ITU-T study group 16, IETF, 3GPP/3GPP2, US TIA/EIA, etc. Amitav has 12 US and world-wide patents granted and few more in the pipeline. He had several (24+) publications and tutorials. At present, his main research interest is in intelligent signal processing which is looking at the confluence of pattern recognition and signal processing methods for various applications in speech and computer vision. Biometric Recognition is also one of his current focuses. Amitav is a member of IEEE, ACM, and other professional organizations.

E-Mail: amitavd@microsoft.com