-source TDOA estimation in reverberant audio using angular spectra and clustering. Signal Processing, Elsevier, 2012Elsevier, , 92, pp.1950Elsevier, -1960Elsevier, . <10.1016Elsevier, /j.sigpro.2011 Multi-source TDOA estimation in reverberant audio using angular spectra and clustering
AbstractWe consider the problem of estimating the time differences of arrival (TDOAs) of multiple sources from a two-channel reverberant audio signal. While several clustering-based or angular spectrum-based methods have been proposed in the literature, only relatively small-scale experimental evaluations restricted to either category of methods have been carried out so far. We design and conduct the first large-scale experimental evaluation of these methods and investigate a two-step procedure combining angular spectra and clustering. In addition, we introduce and evaluate five new TDOA estimation methods inspired from signal-to-noise-ratio (SNR) weighting and probabilistic multi-source modeling techniques that have been successful for anechoic TDOA estimation and audio source separation. The results show that clustering-based methods do not improve upon angular spectrum-based methods. For 5 cm microphone spacing, the best TDOA estimation performance is achieved by one of the proposed SNR-based angular spectrum methods. For larger spacing, a variant of the generalized cross-correlation with phase transform (GCC-PHAT) method performs best.
This paper deals with the localization of multiple sources from two-channel mixtures recorded in a reverberant environment. We introduce new angular spectrum-based methods relying on the signal-to-noise ratio (SNR) to estimate the time difference of arrival (TDOA) of each source. We propose and compare five ways of estimating the SNR in each time-frequency point and in each direction, using beamforming techniques and statistical models. Large-scale evaluation considering a high number of situations shows the effectiveness of the proposed approach compared to state-of-the-art angular spectrum-based techniques.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.