Diarization resegmentation in the factor analysis subspace

Author

Sell, Gregory ; Garcia-Romero, Daniel

Author_Institution

Human Language Technol. Center of Excellence, Johns Hopkins Univ., Baltimore, MD, USA

fYear

2015

fDate

19-24 April 2015

Firstpage

4794

Lastpage

4798

Abstract

Resegmentation is an important post-processing step to refine the rough boundaries of diarization systems that rely on segment clustering of an initial uniform segmentation. Past work has primarily used a Viterbi resegmentation with MFCC features for this purpose. In this paper, we examine an algorithm for resegmentation that operates instead in factor analysis subspace. By combining this system with a speaker clustering front-end, we yield a diarization error rate of 11.5% on the CALLHOME conversational telephone speech corpus.

Keywords

speech recognition; CALLHOME conversational telephone speech corpus; MFCC; Viterbi resegmentation; diarization error rate; diarization resegmentation; diarization system; factor analysis subspace; rough boundaries; segment clustering; speaker clustering front-end; uniform segmentation; Clustering algorithms; Density estimation robust algorithm; Error analysis; Feature extraction; Hidden Markov models; Speech; Viterbi algorithm; Speaker diarization; factor analysis; variational Bayes;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on

Conference_Location

South Brisbane, QLD

Type

conf

DOI

10.1109/ICASSP.2015.7178881

Filename

7178881