With the increasing demand for wireless voice services and limited bandwidth resources, it is critical to develop and implement coding techniques which use spectrum efficiently. One approach to increasing system capacity is to lower the bit rate of telephone speech. A typical telephone conversation contains approximately 40% speech and 60% silence or background acoustic noise. A reduction of th...

The accuracy of noise estimation is important for the performance of a speech denoising system. Most noise estimators suffer from either overestimation or underestimation on the noise level. An overestimate on noise magnitude will cause serious speech distortion for speech denoising. Conversely, a great quantity of residual noise will occur when the noise magnitude is underestimated. Accurately...

In speech enhancement, a decision between speech dominant and noise one is important to reduce noise for increasing intelligibility. This paper presents a speech/noise-dominant decision regardless of SNR. In the proposed decision, the influence of noise is reduced by subtracting the noise component. Therefore, the proposed method decides between the speech dominant and noise one accurately. Fro...

A challenging, unsolved problem in the speech recognition community is recognizing speech signals that are corrupted by loud, highly nonstationary noise. One approach to noisy speech recognition is to automatically remove the noise from the cepstrum sequence before feeding it in to a clean speech recognizer. In previous work published in Eurospeech, we showed how a probability model trained on ...

Designing a machine that is capable for understanding human speech and responds properly to speech utterance or spoken language has intrigued speech research community for centuries. Among others, one of the fundamental problems to building speech recognition system is acoustic noise. The performance of speech recognition system significantly degrades in the presence of ambient noise. Backgroun...

In this paper, we apply the noise adaptive speech recognition for noisy speech recognition in non-stationary noise to the situation that acoustic models are trained from noisy speech. We justify it by that the noise adaptive speech recognition includes iterative processes between a noise parameter estimation step and a model adaptation step, which can possibly do non-linear mapping between the ...

When the talker’s face (visual speech) can be seen, speech perception is both facilitated (for congruent visual speech) and interfered with (for incongruent visual speech). The current study investigated whether the degree of these visual speech effects was affected by the presence of an additional irrelevant talking face. In the experiment, auditory speech targets (vCv syllables) were presente...

This paper describes various noise robustness issues in a speech-to-speech translation system. We present quantitative measures for noise robustness in the context of speech recognition accuracy and speech-to-speech translation performance. To enhance noise immunity, we explore two approaches to improve the overall speech-to-speech translation performance. First, a multi-style training techniqu...