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This paper presents a robust speech recognition method based on the HMM composition and decomposition for the noisy reverberant speech. The method realizes an improved user interface such as the user is not encumbered by microphone equipments. The proposed HMM composition is obtained by natural extension of the HMM composition method of an additive noise to that of the convolutional distortion of the reverberation. The HMM composition is conducted by 2 steps: 1)Composition of HMMs of a speech 組 dacoustical 仕組sferfunction in the cepstrum domain, 2)Composition of the distorted speech and noise HMMs in the linear spectral domain. Furthermore the paper proposes a novel estimation algorithm of acoustical transfer function based on HMM decomposition. The speaker dependent/independent word recognition experiments are carried out using the speech database contaminated by the additive noise and convolutional distortion of the reverberation. These resu1ts clarified the effectiveness of the proposed method.

ADAPTATION OF MODEL PARAMETERS TO DISTORTED SPEECH IN ADVERSE ENVIRONMENTS BY HMM DE/COMPOSITION