Minimum variance method by aggregated microphones

Matsumoto, Mitsuharu; Hashimoto, Shuji

doi:10.1109/isspa.2005.1581079

Cited by 3 publications

(1 citation statement)

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“…Correspondingly, the authors proposed another type of microphone array that does not utilize the phase difference of each microphone but utilizes the directivities of microphones located at the same place, namely aggregated microphones. [17][18][19] In this method, all microphones are located in the same position, and directional microphones are arranged to differentiate the amplitude gains. Hence, the system can easily be miniaturized.…”

Section: Introductionmentioning

confidence: 99%

Blind identification of aggregated microphones in time domain

Matsumoto

Hashimoto

2007

The Journal of the Acoustical Society of America

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This paper introduces an algorithm for blind identification of aggregated microphones in time domain. The features of our approach are summarized as follows: (1) The proposed method treats the blind identification problem of anechoic mixtures in the time domain. (2) The proposed method can identify the gain of each microphone for the directions of sounds whose number is more than the number of the microphones. (3) The proposed method does not utilize the statistical independence of the sounds. The sounds may be not only statistically independent but may also be statistically dependent. (4) The proposed method treats the partially disjoint sounds in the time domain. The sounds may overlap in the frequency domain unlike the sparseness approach. (5) The proposed method does not need to estimate the intervals where sounds are disjoint. First, it is shown that the problem of blind identification and blind source separation can be described not as a convolutive model, but as an instantaneous model in the case of the anechoic mixing when aggregated microphones are assumed. The necessary conditions and the algorithm with experimental results are also described.

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Section: Introductionmentioning

confidence: 99%