Name
Title | ||
|---|---|---|
TDOA Estimation for Multiple Sound Sources in Noisy and Reverberant Environments Using Broadband Independent Component Analysis |
Abstract | ||
|---|---|---|
In this paper, we show that minimization of the statistical dependence using broadband independent component analysis (ICA) can be successfully exploited for acoustic source localization. As the ICA signal model inherently accounts for the presence of several sources and multiple sound propagation paths, the ICA criterion offers a theoretically more rigorous framework than conventional techniques based on an idealized single-path and single-source signal model. This leads to algorithms which outperform other localization methods, especially in the presence of multiple simultaneously active sound sources and under adverse conditions, notably in reverberant environments. Three methods are investigated to extract the time difference of arrival (TDOA) information contained in the filters of a two-channel broadband ICA scheme. While for the first, the blind system identification (BSI) approach, the number of sources should be restricted to the number of sensors, the other methods, the averaged directivity pattern (ADP) and composite mapped filter (CMF) approaches can be used even when the number of sources exceeds the number of sensors. To allow fast tracking of moving sources, the ICA algorithm operates in block-wise batch mode, with a proportionate weighting of the natural gradient to speed up the convergence of the algorithm. The TDOA estimation accuracy of the proposed schemes is assessed in highly noisy and reverberant environments for two, three, and four stationary noise sources with speech-weighted spectral envelopes as well as for moving real speech sources. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/TASL.2010.2092765 | Audio, Speech, and Language Processing, IEEE Transactions |
Keywords | Field | DocType |
acoustic signal processing,adaptive filters,blind source separation,direction-of-arrival estimation,independent component analysis,microphone arrays,reverberation,speech processing,ICA algorithm,ICA criterion,ICA signal model,TDOA estimation,acoustic source localization,adaptive filter,averaged directivity pattern,blind system identification,block-wise batch mode,broadband independent component analysis,composite mapped filter,microphone array,moving real speech source,moving source tracking,noisy environment,reverberant environment,single-path signal model,single-source signal model,sound propagation path,sound source,speech-weighted spectral envelope,stationary noise source,statistical dependence minimization,time difference of arrival,two-channel broadband ICA scheme,Acoustic source localization,adaptive filters,independent component analysis,microphone arrays,reverberation,time difference of arrival (TDOA) estimation | Weighting,Reverberation,Pattern recognition,Computer science,Speech recognition,Independent component analysis,Artificial intelligence,Adaptive filter,Multilateration,System identification,Blind signal separation,Acoustic source localization | Journal |
Volume | Issue | ISSN |
19 | 6 | 1558-7916 |
Citations | PageRank | References |
23 | 1.13 | 25 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lombard, A. | 1 | 23 | 1.13 |
| Yuanhang Zheng | 2 | 58 | 4.24 |
| Herbert Buchner | 3 | 435 | 40.57 |
| W. Kellermann | 4 | 686 | 71.03 |