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Acoustic Source Direction by Hemisphere Sampling

Acoustic Source Direction by Hemisphere Sampling. Stanley T. Birchfield Daniel K. Gillmor Quindi Corporation Palo Alto, California. The Problem. sound source. q. f. compact microphone array. Previous Work.

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Acoustic Source Direction by Hemisphere Sampling

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  1. Acoustic Source Direction by Hemisphere Sampling Stanley T. Birchfield Daniel K. Gillmor Quindi Corporation Palo Alto, California

  2. The Problem sound source q f compact microphone array

  3. Previous Work • two microphones  f[Huang et al., ICASSP 1999; Stephenne and Champagne, ICASSP 1995] • four microphones  q, f[Brandstein et al., ICASSP 1995; Brandstein and Silverman, CSL 1997] • large microphone arrays  r, q, f[Brandstein et al., ICASSP 1995; Svaizer et al., ICASSP 1997]

  4. Our microphone array setup microphone d=15cm Note: Arbitrary compact configurations can be handled

  5. Principle of Least Commitment Principle of Least Commitment: “Delay decisions as long as possible” Example:

  6. Previous Algorithm: Cone Intersection decision is made early mic1 signal prefilter find peak correlate mic2 signal prefilter q,f intersect (may be no intersection) mic3 signal prefilter find peak correlate mic4 signal prefilter [Brandstein et al., ICASSP 1995; Brandstein and Silverman, CSL 1997]

  7. Our Algorithm: Sampled Hemisphere map to common coordinate system mic1 signal prefilter correlate sampled hemisphere mic2 signal prefilter correlate final sampled hemisphere … correlate q,f find peak combine correlate correlate temporal smoothing map to common coordinate system mic3 signal prefilter correlate mic4 signal prefilter decision is made after combining all the available evidence

  8. Pair-wise matching of signals microphone mic1 and mic2 mic3 and mic4 all four mics

  9. Sampled Hemisphere asymptotical cones (black regions are theoretical “blind spots”, where cones have no intersection;practical blind spots are larger) sampled hemisphere

  10. Maximum error from matching non-coincident microphones • additional robustness outweighs possible error, which is negligible (less than 5 degrees when r > 4d)

  11. Experimental results(two trials, A and B) A B A B A B Note: also has been extensively used (hundreds of hours) in real environments

  12. Summary • Advantages of sampled hemisphere algorithm • handles arbitrary microphone array configurations • has no “blind spots” • demonstrates increased robustness, by followingthe principle of least commitment • Future work • integrate into a sound source location system • investigate multiple simultaneous sound sources

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