Improved speech recognition using a subspace projection approach

Philipos C. Loizou; Andreas S. Spanias

doi:10.1109/89.759044

Improved speech recognition using a subspace projection approach

Philipos C. Loizou
, Andreas S. Spanias

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

9 Scopus citations

Abstract

Two class-separability criteria based on the divergence measure are proposed to improve speech recognition performance. The average and weighted average divergence measures are used as criteria for finding a transformation matrix which maps the original features into a more discriminative subspace. Results are presented for a highly confusable task.

Original language	English (US)
Pages (from-to)	343-345
Number of pages	3
Journal	IEEE Transactions on Speech and Audio Processing
Volume	7
Issue number	3
DOIs	https://doi.org/10.1109/89.759044
State	Published - 1999
Externally published	Yes

ASJC Scopus subject areas

Software
Acoustics and Ultrasonics
Computer Vision and Pattern Recognition
Electrical and Electronic Engineering

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10.1109/89.759044

Cite this

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title = "Improved speech recognition using a subspace projection approach",

abstract = "Two class-separability criteria based on the divergence measure are proposed to improve speech recognition performance. The average and weighted average divergence measures are used as criteria for finding a transformation matrix which maps the original features into a more discriminative subspace. Results are presented for a highly confusable task.",

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year = "1999",

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pages = "343--345",

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AU - Loizou, Philipos C.

AU - Spanias, Andreas S.

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AB - Two class-separability criteria based on the divergence measure are proposed to improve speech recognition performance. The average and weighted average divergence measures are used as criteria for finding a transformation matrix which maps the original features into a more discriminative subspace. Results are presented for a highly confusable task.

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Improved speech recognition using a subspace projection approach

Abstract

ASJC Scopus subject areas

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