Technical Program

Paper Detail

Paper:	SLP-P21.10
Session:	Speech Detection, Enhancement and Analysis
Time:	Friday, May 19, 16:30 - 18:30
Presentation:	Poster
Topic:	Speech and Spoken Language Processing: Speech Analysis
Title:	Detecting High Level Dialog Structure without Lexical Information
Authors:	Matthew Aylett, University of California, Berkeley / University of Edinburgh, United Kingdom
Abstract:	The potentially enormous audio resources now available to both organizations, and on the Internet, present a serious challenge to audio browsing technology. In this paper we outline a set of techniques that can be used to determine high level dialog structure without the requirement of resource intensive automatic speech recognition (ASR). Using syllable finding algorithms based on band pass energy together with prosodic feature extraction, we show that a sub-lexical approach to prosodic analysis can out-perform results based on ASR and even those based on a word alignment which requires a complete transcription. We consider how these techniques could be integrated into ASR technology and suggest a framework for extending this type of sub-lexical prosodic analysis.