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

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Presentation on theme: "A Acoustic Source Direction by Hemisphere Sampling Stanley T. Birchfield Daniel K. Gillmor Quindi Corporation Palo Alto, California."— Presentation transcript:

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

2 a 5/11/01 The Problem compact microphone array   sound source

3 a 5/11/01 Previous Work  two microphones   [Huang et al., ICASSP 1999; Stephenne and Champagne, ICASSP 1995]  four microphones   [Brandstein et al., ICASSP 1995; Brandstein and Silverman, CSL 1997]  large microphone arrays   [Brandstein et al., ICASSP 1995; Svaizer et al., ICASSP 1997]

4 a 5/11/01 Our microphone array setup Note: Arbitrary compact configurations can be handled microphone d=15cm

5 a 5/11/01 Principle of Least Commitment Principle of Least Commitment: “Delay decisions as long as possible” Example:

6 a 5/11/01 Previous Algorithm: Cone Intersection mic1 signal correlate find peak mic2 signal prefilter mic3 signal correlate find peak mic4 signal prefilter intersect  (may be no intersection) [Brandstein et al., ICASSP 1995; Brandstein and Silverman, CSL 1997] decision is made early

7 a 5/11/01 Our Algorithm: Sampled Hemisphere mic1 signal correlate map to common coordinate system sampled hemisphere combine temporal smoothing mic2 signal prefilter mic3 signal correlate map to common coordinate system mic4 signal prefilter final sampled hemisphere correlate … find peak  decision is made after combining all the available evidence

8 a 5/11/01 Pair-wise matching of signals microphone mic1 and mic2mic3 and mic4 all four mics

9 a 5/11/01 Sampled Hemisphere asymptotical cones (black regions are theoretical “blind spots”, where cones have no intersection; practical blind spots are larger) sampled hemisphere

10 a 5/11/01 Maximum error from matching non-coincident microphones  additional robustness outweighs possible error, which is negligible (less than 5 degrees when  > 4d)

11 a 5/11/01 Experimental results (two trials, A and B) AAABBB Note: also has been extensively used (hundreds of hours) in real environments

12 a 5/11/01 Summary  Advantages of sampled hemisphere algorithm –handles arbitrary microphone array configurations –has no “blind spots” –demonstrates increased robustness, by following the principle of least commitment  Future work –integrate into a sound source location system –investigate multiple simultaneous sound sources


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