Noise and room acoustics distorted speech recognition by HMM composition

This paper presents a robust speech recognition method based on the HMM composition for the noisy room acoustics distorted 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 naturally extending the HMM composition method of an additive noise to that of the convolutional room acoustics distortion. The HMM composition is conducted by 2 steps: 1)Composition of HMMs of a speech and acoustical transfer function in cepstrum domain, 2)Composition of distorted speech and noise HMMs in linear spectral domain. The speaker dependent/independent word recognition experiments are carried out using the speech database contaminated by the additive noise and convolutional room acoustics distortion. The evaluation experiments are also conducted for unknown testing sound source positions. These results clarified the effectiveness of the proposed method.