Robust speech recognition in car environments
نویسندگان
چکیده
A user-friendly speech interface in a car cabin is highly needed for safety reasons. This paper will describe a robust speech recognition method that can cope with additive noises and multiplicative distortions. A known additive noise, a source signal of which is available, might be canceled by NLMSVAD(Normalized Least Mean Squares with frame-wise Voice Activity Detection). On the other hand, an unknown additive noise, a source signal of which is not available, is suppressed with CSS(Continuous Spectral Subtraction). Furthermore, various multiplicative distortions are simultaneously compensated with ECMN(Exact Cepstrum Mean Normalization) which is speakerdependent/environment-dependent CMN for speech/non-speech. Evaluation results of the proposed method for car cabin environments are finally described.
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