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A speech dereverberation method is proposed that is robust against background noise. In contrast to conventional methods based on the linear prediction of the given microphone input signal, in which the linear prediction coefficients are not fully optimized when there is background noise, the proposed method optimizes the coefficients by linear prediction(More)
A new method for solving the adaptive-group-testing probis proposed. To solve the problem that the conventional method for non-adaptive group testing by Boolean compressive sensing needs a larger number of tests when the pool size is not optimized, the proposed method controls the pool size for each test. The control criterion is the expected information(More)
A dereverberation technique has been developed that optimally combines multichannel inverse filtering (MIF), beamforming (BF), and non-linear reverberation suppression (NRS). It is robust against acoustic transfer function (ATF) fluctuations and creates less distortion than the NRS alone. The three components are optimally combined from a probabilistic(More)
In this paper, we propose a multichannel speech dereverberation and separation technique which is effective even when there are multiple speakers and each speaker's transfer function is time-varying due to fluctuation of the corresponding speaker's head. For robustness against fluctuation, the proposed method optimizes linear filtering with non-linear(More)
In this paper, we propose a head-orientation estimation method from multichannel acoustic signals. Sharpness of a DOA histogram which is extracted by using the sparseness based DOA estimation method varies depending on the head orientation of a speaker. The proposed method utilizes this phenomenon to estimate the head orientation of the speaker. The(More)
This paper deals with speech enhancement problems for highly time-varying systems. For high noise-reduction performance with little speech distortion, cascade methods of various linear/non-linear filters can be easily conceived of, but cascade methods are partial optimizations and cause interferences between filters, because an optimized output signal of a(More)
We propose an optimized speech enhancement method that combines acoustic echo reduction, speech dereverberation, and noise reduction in a unified framework. Normally, partial optimization of acoustic echo reduction, speech dereverberation, and noise reduction does not lead to total optimization. A cascade method of multiple functions causes mutual(More)
We propose a novel non-stationary and convolutive noise reduction method under reverberant environments. Unlike many multichannel noise reduction methods, the proposed method does not need pre knowledge of impulse response or direction of arrival (DOA) of the target source. The proposed method is composed of two processes. On the noise reduction process,(More)