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This paper describes a novel algorithm to improve the performance of sparsity based single-channel speech separation(SCSS) problem based on compressed sensing which is an emerging technique for efficient data reconstruction. The conventional approach assumes the mixing conditions and source signals are stationary. For practical applications of audio source separation, however, we face the challenges...
Noise and residual crosstalk are two important issues that have to be addressed in practical applications of underdetermined blind source separation (UBSS) for speech mixture. This paper proposes a noise-robust UBSS algorithm to deal with highly overlapped speech sources with residual crosstalk suppression scheme in the short-time Fourier transform (STFT) domain. The proposed algorithm is firstly...
In this paper, an automatic speech recognition (ASR) system under ubiquitous environment is proposed, which is successfully implemented in a personalized voice command system under vehicle and living room environment. The proposed ASR system describes a novel scheme of separating speech sources from multi-speakers, detecting speech presence/absence by tracking the higher portion of speech power spectrum...
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