Bayesian fusion of confidence measures for speech recognition

Tae Yoon Kim; Hanseok Ko

doi:10.1109/LSP.2005.859494

Bayesian fusion of confidence measures for speech recognition

Tae Yoon Kim, Hanseok Ko

School of Electrical Engineering

Research output: Contribution to journal › Article › peer-review

13 Citations (Scopus)

Abstract

The application of Bayesian fusion of confidence measures to speech recognition is proposed. Feature level, decision level, and hybrid fusion are considered under the Bayesian framework. The use of speaker-adapted feature-level Bayesian fusion reduced the error rate by 19.4% as compared to the conventional single feature-based confidence scoring in an isolated word out-of-vocabulary rejection test. The decision-level Bayesian fusion also showed better performance than the majority rule. Finally, hybrid Bayesian fusion, which can combine both confidence measure features and local decisions, achieved the best performance.

Original language	English
Pages (from-to)	871-874
Number of pages	4
Journal	IEEE Signal Processing Letters
Volume	12
Issue number	12
DOIs	https://doi.org/10.1109/LSP.2005.859494
Publication status	Published - 2005 Dec

Keywords

Adaptive confidence scoring
Bayesian fusion
Confidence measure (CM)
Speech recognition

ASJC Scopus subject areas

Signal Processing
Electrical and Electronic Engineering
Applied Mathematics

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10.1109/LSP.2005.859494

Cite this

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abstract = "The application of Bayesian fusion of confidence measures to speech recognition is proposed. Feature level, decision level, and hybrid fusion are considered under the Bayesian framework. The use of speaker-adapted feature-level Bayesian fusion reduced the error rate by 19.4% as compared to the conventional single feature-based confidence scoring in an isolated word out-of-vocabulary rejection test. The decision-level Bayesian fusion also showed better performance than the majority rule. Finally, hybrid Bayesian fusion, which can combine both confidence measure features and local decisions, achieved the best performance.",

keywords = "Adaptive confidence scoring, Bayesian fusion, Confidence measure (CM), Speech recognition",

author = "Kim, {Tae Yoon} and Hanseok Ko",

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Bayesian fusion of confidence measures for speech recognition

Abstract

Keywords

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