Accession Number:

ADA525859

Title:

Speaker Indexing in Large Audio Databases Using Anchor Models

Descriptive Note:

Conference paper

Corporate Author:

MASSACHUSETTS INST OF TECH LEXINGTON LINCOLN LAB

Report Date:

2001-01-01

Pagination or Media Count:

5.0

Abstract:

This paper introduces the technique of anchor modeling in the applications of speaker detection and speaker indexing. The anchor modeling algorithm is refined by pruning the number of models needed. The system is applied to the speaker detection problem where its performance is shown to fall short of the state-of-the-art Gaussian Mixture Model with Universal Background Model GMM-UBM system. However, it is further shown that its computational efficiency lends itself to speaker indexing for searching large audio databases for desired speakers. Here, excessive computation may prohibit the use of the GMM-UBM recognition system. Finally, the paper presents a method for cascading anchor model and GMM-UBM detectors for speaker indexing. This approach benefits from the efficiency of anchor modeling and high accuracy of GMM-UBM recognition.

Subject Categories:

  • Information Science
  • Voice Communications

Distribution Statement:

APPROVED FOR PUBLIC RELEASE