We present noise robust automatic speech recognition (ASR) using sparseness-based underdetermined blind source separation (BSS) technique. As a representative underdetermined BSS method, we utilized time-frequency masking in this paper. Although time-frequency masking is able to separate target speech from interferences effectively, one should consider two problems. One is that masking does not...

This study proposes an approach to improve the perceptual quality of speech separated by binary masking through the use of reconstruction in the time-frequency domain. Non-negative matrix factorization and sparse reconstruction approaches are investigated, both using a linear combination of basis vectors to represent a signal. In this approach, the short-time Fourier transform (STFT) of separat...

We propose a novel method for blind speech separation using continuous time-frequency masking. The method is equipped with an adaptive choice of a threshold parameter that is based on utilization of ICA methods. We present a direct application that consists in the speech segregation for automatic transcription of spoken broadcasts disturbed by background music. Experimental results show improve...

\Ve propose a new method for robust image registrat,ion called 'Selective Correlation Coefficient (SCC)' in order to search images under illconditioned illuminat,ion or partial occlusion. A correlation mask image is generated for selecting pixels of a image before matching. The mask image can be derived from a binary-coded increment sign image defined from any object image and the template imag...

Ideal Binary Masking (IdBM) is considered as the primary goal of computational auditory scene analysis. This binary masking criterion provides a time-frequency representation of noisy speech and retains regions where the speech dominates the noise while discarding regions where the noise is dominant. Several studies have shown the benefits of IdBM for normal hearing and hearing-impaired listene...

Technical limitations in image capturing usually impose defective, such as contrast degradation. There are different approaches to improve the contrast of an image. Among the exiting approaches, un-sharp masking is a popular method due to its simplicity in implementation and computation. There is an important parameter in un-sharp masking, named gain factor, which affects the quality of the enh...

In this paper, we formulate the face hallucination as an image decomposition problem, and propose a Morphological Component Analysis (MCA) based method for hallucinating a single face image. A novel three-step framework is presented for the proposed method. Firstly, a low-resolution input image is up-sampled via an interpolation. Then, the interpolated image is decomposed into a global high-res...

In this paper, we present a wavelet coefficients masking based on Local Binary Patterns (WLBP) approach to enhance the temporal spectra of the wavelet coefficients for speech enhancement. This technique exploits the wavelet denoising scheme, which splits the degraded speech into pyramidal subband components and extracts frequency information without losing temporal information. Speech enhanceme...

Speech intelligibility in reverberant environments is reduced because of overlap-masking. Signal modification prior to presentation in such listening environments, e.g., with a public announcement system, can be employed to alleviate this problem. Time-scale modifications are particularly effective in reducing the effect of overlap-masking. A method for introducing linguistically-motivated paus...