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Beamforming using sensor array is widely used in spatial signal processing since it offers better spatial focusing capability than single sensor. However, in practical applications for broadband signal, there always exists a trade-off issue between the directivity capability of an array and its robustness on system errors. In this paper, in order to combine merits of different beamformers instead...
This paper presented a robust sound recognition work applied to awareness for health/children/elderly care. Specific sound awareness services can be activated based on recognized sound classes for detecting human activities as health care. To attain this goal, this study developed key technologies as follows: 1) SNR-aware subspace signal enhancement, 2) pitch and power density-based sound/speech discrimination,...
Noise reduction is a fundamental requirement of many speech applications. Sometimes the major interferences, such as music, song, cross-talking, etc., coming from loudspeakers nearby make it a more challenging problem. In this paper, by supposing the locations of interferences are fixed, a semi-blind Degenerate Unmixing Estimation Technique (DUET) approach using dual-microphone is proposed. Firstly,...
Speech enhancement under nonstationary environments is a challenging problem. This paper addresses the problem of speech presence probability (SPP) estimation. According to the fact that speech is approximately sparse in time-frequency domain, we integrate time and frequency minimum tracking results to estimate the noise power spectral density and the a posteriori signal-to-noise ratio. A sparseness...
This paper proposes a new noise estimation algorithm to reduce the estimation delays under highly non-stationary noise conditions. Since the harmonic ripples appeared in the spectrogram are valuable for human to localize the speech presence, based on the characteristics of these ripples, we propose a novel energy independent feature to detect the changing noise. If noise is present, the noise floors...
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