The SRI-ICSI Spring 2007 meeting and lecture recognition system
Andreas Stolcke, Xavier Anguera, Kofi Boakye, Özgür Çetin, Adam L. Janin, Mathew Magimai.-Doss, Chuck Wooters, Jing Wen Zheng · 2008
Abstract. We describe the latest version of the SRI-ICSI meeting and lecture recognition system, as was used in the NIST RT-07 evaluations, highlighting improvements made over the last year. Changes in the acoustic preprocessing include updated beamforming software for processing of multiple distant mi-crophones, and various adjustments to the speech segmenter for close-talking microphones. Acoustic models were improved by the combined use of neural-net-estimated phone posterior features, discriminative feature transforms trained with fMPE-MAP, and discriminative Gaussian estimation using MPE-MAP, as well as model adaptation specifically to nonnative and non-American speakers. The net effect of these enhancements was a 14-16 % relative error reduction on distant microphones, and a 16-17 % error reduction on close-talking microphones. Also, for the first time, we report results on a new “coffee break ” meeting genre, and on a new NIST metric designed to evaluate combined speech diarization and recognition. 1