ScholarLens Back to search
1991•Unpublished venueRequires access

On speaker-independent, speaker-dependent, and speaker-adaptive speech recognition

Xuedong Huang, K.-F. Lee

Open publisher page 17 citations

Abstract

The DARPA Resource Management task is used as the domain to investigate the performance of speaker-independent, speaker-dependent, and speaker-adaptive speech recognition. The authors already have a state-of-the-art speaker-independent speech recognition system, SPHINX. The error rate for RM2 test set is 4.3%. They extended SPHINX to speaker-dependent speech recognition. The error rate is reduced to 1.4-2.6% with 600-2400 training sentences for each speaker, which demonstrated a substantial difference between speaker-dependent and -independent systems. Based on speaker-independent models, a study was made of speaker-adaptive speech recognition. With 40 adaptation sentences for each speaker, the error rate can be reduced from 4.3% to 3.1%.>

About this research paper

What this paper is about

The DARPA Resource Management task is used as the domain to investigate the performance of speaker-independent, speaker-dependent, and speaker-adaptive speech recognition. The authors already have a state-of-the-art speaker-independent speech recognition system, SPHINX. The error rate for RM2 test set is 4.3%. They extended SPHINX to speaker-dependent speech recognition. The error rate is reduced to 1.4-2.6% with 600-2400 training sentences for each speaker, which demonstrated a substantial difference between speaker-dependent and -independent systems. Based on speaker-independent models, a study was made of speaker-adaptive speech recognition. With 40 adaptation sentences for each speaker, the error rate can be reduced from 4.3% to 3.1%.>

Why it matters

OpenAlex reports 17 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 DARPA Resource Management task is used as the domain to investigate the performance of speaker-independent, speaker-dependent, and speaker-adaptive speech recognition. The authors already have a state-of-the-art speaker-independent speech recognition system, SPHINX. The error rate for RM2 test set is 4.3%. They extended SPHINX to speaker-dependent speech recognition. The error rate is reduced to 1.4-2.6% with 600-2400 training sentences for each speaker, which demonstrated a substantial difference between speaker-dependent and -independent systems. Based on speaker-independent models, a study was made of speaker-adaptive speech recognition. With 40 adaptation sentences for each speaker, the error rate can be reduced from 4.3% to 3.1%.>

Key concepts: Speech recognition, Speaker recognition, Sphinx, Computer science, Word error rate, Speaker diarisation, Test set, Set (abstract data type)

Related papers

Related paper 1Related paper 2Related paper 3
Back to paper searchBrowse research topicsOriginal source
On speaker-independent, speaker-dependent, and speaker-adaptive speech recognition — Research Paper | ScholarLens