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Speech recognition based on the subspace method: AI class-description leaning viewpoint
1992
Journal of the Acoustical Society of Japan (E)
This paper describes the learning mechanism employed in a highly efficient user-adaptive speech recognizer based on the subspace method for large vocabulary Japanese test input. Comparing the subspace-based learning system with the well-known AI learning system ARCH, the following points are made:(1) Subspace learning using covariance matrix modification and KL-expansion is a kind of class-description learning from examples, as found in ARCH. The subspace learning method focusses on feature
doi:10.1250/ast.13.429
fatcat:gi7dig43yramrkposi7ajkygou