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Journal Articles IEEE Transactions on Audio, Speech and Language Processing Year : 2014

A Geometric Approach to Sound Source Localization from Time-Delay Estimates


This paper addresses the problem of sound-source localization from time-delay estimates using arbitrarily-shaped non-coplanar microphone arrays. A novel geometric formulation is proposed, together with a thorough algebraic analysis and a global optimization solver. The proposed model is thoroughly described and evaluated. The geometric analysis, stemming from the direct acoustic propagation model, leads to necessary and sufficient conditions for a set of time delays to correspond to a unique position in the source space. Such sets of time delays are referred to as feasible sets. We formally prove that every feasible set corresponds to exactly one position in the source space, whose value can be recovered using a closed-form localization mapping. Therefore we seek for the optimal feasible set of time delays given, as input, the received microphone signals. This time delay estimation problem is naturally cast into a programming task, constrained by the feasibility conditions derived from the geometric analysis. A global branch-and-bound optimization technique is proposed to solve the problem at hand, hence estimating the best set of feasible time delays and, subsequently, localizing the sound source. Extensive experiments with both simulated and real data are reported; we compare our methodology to four state-of-the-art techniques. This comparison shows that the proposed method combined with the branch-and-bound algorithm outperforms existing methods. These in-depth geometric understanding, practical algorithms, and encouraging results, open several opportunities for future work.
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Dates and versions

hal-00910081 , version 1 (27-11-2013)
hal-00910081 , version 2 (26-02-2014)
hal-00910081 , version 3 (08-04-2014)



Xavier Alameda-Pineda, Radu Horaud. A Geometric Approach to Sound Source Localization from Time-Delay Estimates. IEEE Transactions on Audio, Speech and Language Processing, 2014, 22 (6), pp.1082-1095. ⟨10.1109/TASLP.2014.2317989⟩. ⟨hal-00910081v3⟩
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