ScholarLens Back to search
2009•Unpublished venueRequires access

THE SRI NIST 2008 speaker recognition evaluation system

Sachin Kajarekar, Nicolas Scheffer, Martin Graciarena, Elizabeth Shriberg, Andreas Stolcke, Luciana Ferrer, Tobias Bocklet

Open publisher page 50 citations

Abstract

The SRI speaker recognition system for the 2008 NIST speaker recognition evaluation (SRE) incorporates a variety of models and features, both cepstral and stylistic. We highlight the improvements made to specific subsystems and analyze the performance of various subsystem combinations in different data conditions. We show the importance of language and nativeness conditioning, as well as the role of ASR for speaker verification.

About this research paper

What this paper is about

The SRI speaker recognition system for the 2008 NIST speaker recognition evaluation (SRE) incorporates a variety of models and features, both cepstral and stylistic. We highlight the improvements made to specific subsystems and analyze the performance of various subsystem combinations in different data conditions. We show the importance of language and nativeness conditioning, as well as the role of ASR for speaker verification.

Why it matters

OpenAlex reports 50 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

The SRI speaker recognition system for the 2008 NIST speaker recognition evaluation (SRE) incorporates a variety of models and features, both cepstral and stylistic. We highlight the improvements made to specific subsystems and analyze the performance of various subsystem combinations in different data conditions. We show the importance of language and nativeness conditioning, as well as the role of ASR for speaker verification.

Key concepts: NIST, Speaker recognition, Computer science, Speech recognition, Variety (cybernetics), Mel-frequency cepstrum, Speaker diarisation, Cepstrum

Related papers

Related paper 1Related paper 2Related paper 3
Back to paper searchBrowse research topicsOriginal source
THE SRI NIST 2008 speaker recognition evaluation system — Research Paper | ScholarLens