Conference Paper

Blind alignment of asynchronously recorded signals for distributed microphone array

Grad. Sch. of Inf. Sci. & Technol., Univ. of Tokyo, Tokyo, Japan
DOI: 10.1109/ASPAA.2009.5346505 Conference: Applications of Signal Processing to Audio and Acoustics, 2009. WASPAA '09. IEEE Workshop on
Source: IEEE Xplore


In this paper, aiming to utilize independent recording devices as a distributed microphone array, we present a novel method for alignment of recorded signals with localizing microphones and sources. Unlike conventional microphone array, signals recorded by independent devices have different origins of time, and microphone positions are generally unknown. In order to estimate both of them from only recorded signals, time differences between channels for each source are detected, which still include the differences of time origins, and an objective function defined by their square errors is minimized. For that, simple iterative update rules are derived through auxiliary function approach. The validity of our approach is evaluated by simulative experiment.

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Available from: Shigeki Sagayama,
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    • "A challenge in such ad-hoc arrays is that the locations of the microphones are generally unknown and there is no precise temporal synchronization between the microphones . Traditional microphone-array techniques, such as beamforming and sound source localization, which rely on the knowledge of microphone positions and assume samplesynchronized audio channels, cannot be applied directly [2] [3]. "
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    ABSTRACT: We use audio fingerprinting to solve the synchronization problem between multiple recordings from an ad-hoc array consisting of randomly placed wireless microphones or hand-held smartphones. Synchronization is crucial when employing conventional microphone array techniques such as beamforming and source localization. We propose a fine audio landmark fingerprinting method that detects the time difference of arrivals (TDOAs) of multiple sources in the acoustic environment. By estimating the maximum and minimum TDOAs, the proposed method can accurately calculate the unknown time offset between a pair of microphone recordings. Experimental results demonstrate that the proposed method significantly improves the synchronization accuracy of conventional audio fingerprinting methods and achieves comparable performance to the generalized cross-correlation method.
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    • "2.3. Determinedness As pointed out in [8] "
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    • "Several solutions to localization based on the TDOA have been proposed. Some are iterative methods based on leastsquares criteria [4] [9] [10] [11] [12] or a maximum likelihood principle [3] [13] [14] [15], and some are non-iterative methods [16] [17]. Generally, since the cost functions used in the iterative methods are nonlinear and nonconvex, they can be easily trapped at local minima. "
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    ABSTRACT: In this paper, we present a new method to find solutions to the time difference of arrival (TDOA)-based source and sensor localization problem. This paper is a continuation of [1], in which sources and sensors are localized on the basis of time of arrival (TOA) measurements. Generally, the TOA is known if the TDOA and reference-distances with the sound velocity are given, where the reference-distances are defined as the distances from the first (reference) sensor to the sources. We show that when the numbers of sources and sensors are at least six and eight, respectively, the reference-distances can be computed directly from TDOA measurements. This means that in such cases, the positions of the sources and sensors can be directly estimated in closed-form solutions, except for one reference-distance, which is estimated by a grid search. The validity of our algorithm is evaluated by synthetic experiments in noise-free and noisy cases.
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