Automatic Transcription of Real World Data – Ponani S. Gopalakrishnan (IBM TJ Watson Research Center)

April 15, 1997 all-day

Research effort in speech recognition is moving towards transcription of more realistic data sources. At IBM we have been examining acoustic modeling issues in the context of broadcast news transcription. This data exhibit many of the problems we encounter in speech recognition, including a variety of speaking styles, different signal and background conditions and a variety of topics. In this talk we will highlight some of the issues in automatically transcribing such varied sources. We will discuss some of the acoustic modeling issues we have been examining, including rapid adaptation techniques, and present results on this and other large vocabulary speech recognition tasks.

Johns Hopkins University

Johns Hopkins University, Whiting School of Engineering

Center for Language and Speech Processing
Hackerman 226
3400 North Charles Street, Baltimore, MD 21218-2680

Center for Language and Speech Processing