A new speech enhancement scheme is presented integrating spatial and temporal signal processing methods for robust speech recognition in noisy environments. The scheme first separates spatially localized point sources from noisy speech signals recorded by two microphones. Blind source separation algorithms assuming no a priori knowledge about the sources involved are applied in this spatial pro...

A new speech enhancement scheme is presented integrating spatial and temporal signal processing methods for robust speech recognition in noisy environments. The scheme first separates spatially localized point sources from noisy speech signals recorded by two microphones. Blind source separation algorithms assuming no a priori knowledge about the sources involved are applied in this spatial pro...

In this paper, we investigate the effectiveness of phase for speaker recognition in noisy conditions and combine the phase information with mel-frequency cepstral coefficients (MFCCs). To date, almost speaker recognition methods are based on MFCCs even in noisy conditions. For MFCCs which dominantly capture vocal tract information, only the magnitude of the Fourier Transform of time-domain spee...

Traditional noise reduction systems modify a noisy signal to make it more like the original clean signal. For speech, these methods suffer from two main problems: under-suppression of noise and over-suppression of target speech. Instead, synthesizing clean speech based on the noisy signal could produce outputs that are both noise-free and high quality. Our previous work introduced such a system...

The growth of the cellular technology and wireless networks all over the world has increased the demand for digital information by manifold. This massive demand poses difficulties for handling huge amounts of data that need to be stored and transferred. To overcome this problem we can compress the information by removing the redundancies present in it. Redundancies are the major source of gener...