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A Study on Manifolds of Acoustic Responses

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Latent Variable Analysis and Signal Separation (LVA/ICA 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9237))

Abstract

The construction of a meaningful metric between acoustic responses which respects the source locations, is addressed. By comparing three alternative distance measures, we verify the existence of the acoustic manifold and give an insight into its nonlinear structure. From such a geometric view point, we demonstrate the limitations of linear approaches to infer physical adjacencies. Instead, we introduce the diffusion framework, which combines local and global processing in order to find an intrinsic nonlinear embedding of the data on a low-dimensional manifold. We present the diffusion distance which is related to the geodesic distance on the manifold. In particular, simulation results demonstrate the ability of the diffusion distance to organize the samples according to the source direction of arrival (DOA).

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References

  1. Allen, J.B., Berkley, D.A.: Image method for efficiently simulating small room acoustics. J. Acoust. Soc. Am. 65(4), 943–950 (1979)

    Article  Google Scholar 

  2. Coifman, R., Lafon, S.: Diffusion maps. Appl. Comput. Harmon. Anal. 21, 5–30 (2006)

    Article  MathSciNet  Google Scholar 

  3. Deleforge, A., Forbes, F., Horaud, R.: Variational EM for binaural sound-source separation and localization. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 76–80 (2013)

    Google Scholar 

  4. Deleforge, A., Forbes, F., Horaud, R.: Acoustic space learning for sound-source separation and localization on binaural manifolds. Int. J. Neural Syst. 25(1), 19 (2015)

    Article  MathSciNet  Google Scholar 

  5. Deleforge, A., Horaud, R.: 2D sound-source localization on the binaural manifold. In: IEEE International Workshop on Machine Learning for Signal Processing (MLSP). Santander, Spain, September 2012

    Google Scholar 

  6. Fozunbal, M., Kalker, T., Schafer, R.W.: Multi-channel echo control by model learning. In: The International Workshop on Acoustic Echo and Noise Control (IWAENC). Seattle, Washington, September 2008

    Google Scholar 

  7. Gannot, S., Burshtein, D., Weinstein, E.: Signal enhancement using beamforming and nonstationarity with applications to speech. IEEE Trans. Signal Process. 49(8), 1614–1626 (2001)

    Article  Google Scholar 

  8. Laufer, B., Talmon, R., Gannot, S.: Relative transfer function modeling for supervised source localization. In: IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA). New Paltz, NY, October 2013

    Google Scholar 

  9. Talmon, R., Cohen, I., Gannot, S., Coifman, R.: Diffusion maps for signal processing: a deeper look at manifold-learning techniques based on kernels and graphs. IEEE Signal Process. Mag. 30(4), 75–86 (2013)

    Article  Google Scholar 

  10. Talmon, R., Gannot, S.: Relative transfer function identification on manifolds for supervised GSC beamformers. In: 21st European Signal Processing Conference (EUSIPCO). Marrakech, Morocco, September 2013

    Google Scholar 

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Correspondence to Sharon Gannot .

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© 2015 Springer International Publishing Switzerland

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Laufer-Goldshtein, B., Talmon, R., Gannot, S. (2015). A Study on Manifolds of Acoustic Responses. In: Vincent, E., Yeredor, A., Koldovský, Z., Tichavský, P. (eds) Latent Variable Analysis and Signal Separation. LVA/ICA 2015. Lecture Notes in Computer Science(), vol 9237. Springer, Cham. https://doi.org/10.1007/978-3-319-22482-4_23

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  • DOI: https://doi.org/10.1007/978-3-319-22482-4_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22481-7

  • Online ISBN: 978-3-319-22482-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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