Accession Number:

ADA444863

Title:

Speaker Segmentation and Clustering Using Gender Information

Descriptive Note:

Conference paper

Corporate Author:

GENERAL DYNAMICS ADVANCED INFORMATION SYSTEMS DAYTON OH

Report Date:

2006-02-01

Pagination or Media Count:

10.0

Abstract:

This paper considers the segmentation and clustering of conversational speech for the two-wire training 3conv2w and two-wire testing 1conv2w conditions of the NIST 2005 Speaker Recognition Evaluation. A notable feature of the system described is that each file is labeled as containing either opposite- or same-gender speakers The speech segments for opposite-gender files are clustered by gender, while those for same-gender files are processed by agglomerative clustering. By using gender information in the clustering of the opposite-gender files, the equal error rate in the 3conv2w training condition was reduced from 15.2 to 9.9. For the 1conv2w testing condition, clustering opposite-gender files by gender did not improve performance over agglomerative clustering however, it was over 100 times faster than agglomerative clustering on the opposite-gender files.

Subject Categories:

  • Voice Communications
  • Linguistics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE