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

ABSTRACT 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, Aug 11, 2015
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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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    • "Several solutions to solve the sound localization based on TOA or Time-Difference-of-Arrival (TDOA) have been proposed . Some are iterative methods based on a least square criteria [1] [2] [3] [4] [5] or a maximum likelihood principle [6] [7] [8] [9], and some are non-iterative methods [10] [11]. Generally, since cost functions used in the iterative methods are nonlinear and non-convex, they can be easily trapped into local minima . "
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    ABSTRACT: This paper presents numerical formulae for the Time-of-Arrival (TOA)-based microphone and source localization problem, which determines the positions of microphones and sources based on distances between each microphone and each source respectively. This is a purely geometrical problem in mathematics. Concretely, we show when the number of microphones or the number of sources is at least nine, the formulae of the microphone positions and source positions are given simply from the distance-matrix. A similar statement is given in the cases of at least eight microphones or sources if we know an extra information about the distance between any two microphones or two sources. The accuracy of these formulae are proven shortly by ten thousand independent experiments of which coordinates of points have an independent Uniform distribution.
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    • "However, the increased freedom of ad hoc microphone arrays raises various issues that do not arise in conventional array signal processing. For example, the array geometry is unknown [2,6–8], the recording devices have different unknown gains [2], each device starts recording independently [7] [8], and the sampling frequencies are not common among the observation channels [9] [10] [11] [12] [13] [14] [15]. Also, in WASNs, the efficiencies of communication and distributed computation are important issues to achieve array signal processing with a limited bandwidth and array nodes with low computational power [5]. "
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    ABSTRACT: In this paper, we propose a novel method for the blind compensation of drift for the asynchronous recording of an ad hoc microphone array. Digital signals simultaneously observed by different recording devices have drift of the time differences between the observation channels because of the sampling frequency mismatch among the devices. On the basis of a model in which the time difference is constant within each short time frame but varies in proportion to the central time of the frame, the effect of the sampling frequency mismatch can be compensated in the short-time Fourier transform (STFT) domain by a linear phase shift. By assuming that the sources are motionless and have stationary amplitudes, the observation is regarded as being stationary when drift does not occur. Thus, we formulate a likelihood to evaluate the stationarity in the STFT domain to evaluate the compensation of drift. The maximum likelihood estimation is obtained effectively by a golden section search. Using the estimated parameters, we compensate the drift by STFT analysis with a noninteger frame shift. The effectiveness of the proposed blind drift compensation method is evaluated in an experiment in which artificial drift is generated.
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