Discriminative Training of Acoustic Models - From MPE to fMPE
Center for Language & Speech Processing(CLSP), JHU via YouTube
The Most Addictive Python and SQL Courses
AI, Data Science & Cloud Certificates from Google, IBM & Meta
Overview
AI, Data Science & Cloud Certificates from Google, IBM & Meta — 40% Off
One plan covers every Professional Certificate on Coursera. 40% off Coursera Plus Annual.
Unlock All Certificates
Learn about discriminative training of acoustic models in this 37-minute lecture from IBM researcher Daniel Povey at Johns Hopkins University's Center for Language & Speech Processing. Gain insights into Maximum Mutual Information Estimation (MPE) techniques and discover fMPE, an innovative feature-space transformation method developed at IBM that maximizes the MPE criterion for acoustic model training.
Syllabus
Old and new work in discriminative training of acoustic models – Daniel Povey (IBM) - 2005
Taught by
Center for Language & Speech Processing(CLSP), JHU