We address the problem of speaker number detection from speech signals of simultaneous speakers, collected by uniform linear microphonearrays (ULAs). Using the signal captured by microphonearray a covariance matrix ...
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ISBN:
(纸本)9781467387897
We address the problem of speaker number detection from speech signals of simultaneous speakers, collected by uniform linear microphonearrays (ULAs). Using the signal captured by microphonearray a covariance matrix can be constructed. To take advantage of the information that covariance matrix provides, we employ eigenvalue decomposition on the covariance matrix. By finding the notable gap between decreasingly sorted eigenvalues of the covariance matrix, the number of the speakers can be determined. While many existent method for speaker number detection are faulty in the presence of the noise, our simulations on different numbers of simultaneous speakers demonstrates the robustness of the proposed method against both noise and reverberation.
In this work, we investigate the efficacy of Micro Electro-Mechanical System (MEMS) microphones, a newly developed technology of very compact sensors, for multichannel speech enhancement. Experiments are conducted on ...
详细信息
In this work, we investigate the efficacy of Micro Electro-Mechanical System (MEMS) microphones, a newly developed technology of very compact sensors, for multichannel speech enhancement. Experiments are conducted on ...
详细信息
ISBN:
(纸本)9781467369985
In this work, we investigate the efficacy of Micro Electro-Mechanical System (MEMS) microphones, a newly developed technology of very compact sensors, for multichannel speech enhancement. Experiments are conducted on real speech data collected using a MEMS microphonearray. First, the effectiveness of the array geometry for noise suppression is explored, using a new corpus containing speech recorded in diffuse and localized noise fields with a MEMS microphonearray configured in linear and hexagonal array geometries. Our results indicate superior performance of the hexagonal geometry. Then, MEMS microphones are compared to Electret Condenser microphones (ECMs), using the ATHENA database, which contains speech recorded in realistic smart home noise conditions with hexagonal-type arrays of both microphone types. MEMS microphones exhibit performance similar to ECMs. Good performance, versatility in placement, small size, and low cost, make MEMS microphones attractive for multichannel speechprocessing.
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