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The speech enhancement architecture presented in this paper is specifically developed for hands-free robot spoken dialog systems. It is designed to take advantage of additional sensors installed inside the robot to record the internal noises. First a modified frequency domain blind signal separation (FD-BSS) gives estimates of the noises generated outside and inside of the robot. Then these noises...
This paper presents a new frequency domain blind signal extraction (FD-BSE) method for the extraction of a target speech in presence of diffuse background noise. This is a fast alternative to frequency domain blind signal separation (FD-BSS) for hands-free speech interface. Like the FD-BSS approach, the speech signal is enhanced by using a nonlinear filter to suppress the noise estimated by the blind...
The model of the human/machine hands-free speech interface is defined as a point source (the user voice) and a diffuse background noise. This situation is very different from the usual cocktail party model, separation of a mixture of speeches, that is usually treated in frequency domain blind signal separation (FD-BSS). In particular, the fast permutation solvers proposed for the cocktail party model...
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