Speech recognition method including biased principal components

G - Physics – 10 – L

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354/54

G10L 9/06 (1985.01)

Patent

CA 1229923

Abstract of the Disclosure A speech recognition method and apparatus employ a speech processing circuitry for repetitively deriving from a speech input, at a frame repetition rate, a plurality of acoustic parameters. The acoustic parameters represent the speech input signal for a frame time. A plurality of template matching and cost processing circuitries are connected to a system bus, along with the speech processing circuitry, for determining, or identifying, the speech units in the input speech, by comparing the acoustic parameters with stored template patterns. The apparatus can be expanded by adding more template matching and cost processing circuitry to the bus thereby increasing the speech recognition capacity of the apparatus. The speech processing circuitry establishes overlapping time durations for generating the acoustic parameters and further employs a sinc-Kaiser smoothing function in combination with a folding technique for providing a discrete Fourier transform. The Fourier spectra are transformed using a biased principal component analysis which optimizes the across class variance. The template matching and cost processing circuitries provide distributed processing, on demand, of the acoustic parameters for generating through a dynamic programming technique the recognition decision.

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