Modeling auditory scene analysis by multidimensional statistical filtering may stimulate advances in hearing-aid signal processing

Authors

  • Volker Hohmann Medical Physics, University of Oldenburg, D-26111Oldenburg, Germany

Abstract

‘Auditory Scene Analysis’ (ASA) denotes the ability of the human auditory system to decode information on sound sources from a superposition of sounds in an extremely robust way. ASA is closely related to the 'Cocktail-Party-Effect' (CPE), i.e., the ability of a listener to perceive speech in adverse conditions at low signal-to-noise ratios. This contribution discusses theoretical and empirical evidence suggesting that robustness of source decoding is partly achieved by exploiting redundancies that are present in the source signals. Redundancies reflect the restricted spectro-temporal dynamics of real source signals, e.g., of speech, and limit the number of possible states of a sound source. In order to exploit them, prior knowledge on the characteristics of a sound source needs to be represented in the decoder/classifier (‘expectation-driven processing’). In a proof-of-concept approach, novel multidimensional statistical ltering algorithms such as ‘particle filters’ have been shown to successfully incorporate prior knowledge on the characteristics of speech and to estimate the dynamics of a speech source from a superposition of speech sounds (Nix and Hohmann, 2007).

References

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Additional Files

Published

2007-12-15

How to Cite

Hohmann, V. (2007). Modeling auditory scene analysis by multidimensional statistical filtering may stimulate advances in hearing-aid signal processing. Proceedings of the International Symposium on Auditory and Audiological Research, 1, 11–20. Retrieved from https://proceedings.isaar.eu/index.php/isaarproc/article/view/2007-02

Issue

Vol. 1 (2007): Auditory Signal Processing in Hearing Impaired Listeners

Section

2007/1. Auditory signal processing and perception

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