Automatic linguistic segmentation of conversational speech

Author

Stolcke, Andreas ; Shriberg, Elizabeth

Author_Institution

Speech Technol. & Res. Lab., SRI Int., Menlo Park, CA, USA

Volume

2

fYear

1996

fDate

3-6 Oct 1996

Firstpage

1005

Abstract

As speech recognition moves toward more unconstrained domains such as conversational speech, we encounter a need to be able to segment (or resegment) waveforms and recognizer output into linguistically meaningful units such a sentences. Toward this end, we present a simple automatic segmenter of transcripts based on N-gram language modeling. We also study the relevance of several word-level features for segmentation performance. Using only word-level information, we achieve 85% recall and 70% precision on linguistic boundary detection

Keywords

linguistics; natural languages; nomograms; speech recognition; N-gram language modeling; automatic linguistic segmentation; conversational speech; linguistic boundary detection; linguistically meaningful units; precision; recall; segmentation performance; speech recognition; speech recognizer output; transcript segmentation; unconstrained domains; waveform segmentation; word-level features; Acoustic signal detection; Acoustic waves; Automatic speech recognition; Decoding; Error analysis; Laboratories; Loudspeakers; Natural languages; Speech processing; Speech recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Spoken Language, 1996. ICSLP 96. Proceedings., Fourth International Conference on

Conference_Location

Philadelphia, PA

Print_ISBN

0-7803-3555-4

Type

conf

DOI

10.1109/ICSLP.1996.607773

Filename

607773