Sentence Boundary Detection in Broadcast Speech Transcripts
Yoshihiko Gotoh, Steve J. Renals · ERA · 2000
This paper presents an approach to identifying sentence boundaries in broadcast speech transcripts. We describe finite state models that extract sentence boundary information statistically from text and audio sources. An n-gram language model is constructed from a collection of British English news broadcasts and scripts. An alternative model is estimated from pause duration information in speech recogniser outputs aligned with their programme script counterparts. Experimental results show that the pause duration model alone outperforms the language modelling approach and that, by combining these two models, it can be improved further and precision and recall scores of over 70% were attained for the task. 1. INTRODUCTION Spoken audio data is a rich information source. Extensive research efforts during past decades have resulted in automatic speech transcription systems that can perform certain tasks (e.g., large vocabulary dictation from a cooperative speaker) with a high degree of a...