When a target-speech/masker mixture is processed with the signal-separation technique, ideal binary mask (IBM), intelligibility of target speech is remarkably improved in both normal-hearing listeners and hearing-impaired listeners. Intelligibility of speech can also be improved by filling in speech gaps with un-modulated broadband noise. This study investigated whether intelligibility of targe...

This paper presents a spectral normalisation based method for extraction of speech robust features in additive noise. The method has two main goals: 1) The “peaked” spectral zones, where the most speech energy is concentrated must be preserved (from clean to noisy speech features) as much as possible by the feature extraction process. Usually, these spectral regions are the most reliable due to...

This paper presents a spectral normalisation based method for extraction of speech robust features in additive noise. The method has two main goals: 1) The “peaked” spectral zones, where the most speech energy is concentrated must be preserved (from clean to noisy speech features) as much as possible by the feature extraction process. Usually, these spectral regions are the most reliable due to...

The performance of a speech recognition system is often degraded due to the mismatch between the environments of development and application. One of the major sources that give rises to this mismatch is additive noise. The approaches for handling the problem of additive noise can be divided into three classes: speech enhancement, robust speech feature extraction, and compensation of speech mode...

In order to reduce background noise in noisy speech, we have investigated a noise reduction method based on a noise reconstruction system (NRS) with an adaptive line enhancer (ALE). The NRS uses a noise reconstruction filter (NRF) estimating the background noise. In case a fixed step size for updating tap coefficients of the NRF is used, it is difficult to estimate the background noise accurate...

Noise cancellation is the process of removing background noise from speech signal. The degradation of speech due to presence of background noise and several other noises cause difficulties in various signal processing tasks like speech recognition, speaker recognition, speaker verification etc. Many methods have been widely used to eliminate noise from speech signal like linear and nonlinear fi...

The main work at Columbia this year has been the development of algorithms for extracting and recognizing speech in nonstationary, noisy environments when only a single microphone channel is available. Our particular approach is based on using trained models to distinguish regions of time-frequency containing speech from nonspeech areas [2], and we have pursued this along several directions: On...