LATTICE RESCORING EXPERIMENTS WITH DURATION MODELS

This paper reports on experiments using phone and word duration models to improve speech recognition accuracy. The duration information is integrated into state-of-the-art large vocabulary speech recognition systems by rescoring word lattices that include phone-level segmentations. Experimental results are given for a conversational telephone speech (CTS) task in French and for the TC-Star EPPS transcription task in Spanish and English. An absolute word error rate reduction of about 0.5% is observed for the CTS task, and smaller but consistent gains are observed for the EPPS task.