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Abstract

A recognition system (10) incorporates a filterbank analyser (16) producing successive data vectors of energy values for twenty-six frequency intervals in a speech signal. A unit (18) compensates for spectral distortion in each vector. Compensated vectors undergo a transformation into feature vectors with twelve dimensions and are matched with hidden Markov model states in a computer (24). Each matched model state has a mean value which is an estimate of the speech feature vector. A match inverter (28) produces an estimate of the speech data vector in frequency space by a pseudo-inverse transformation. It includes information which will be lost in a later transformation to frequency space. The estimated data vector is compared with its associated speech signal data vector, and infinite impulse response filters (44) average their difference with others. Averaged difference vectors so produced are used by the unit (18) in compensation of speech signal data vectors.

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