Computational auditory scene analysis

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Computational auditory scene analysis (CASA) is the study of auditory scene analysis by computational means ^[1]. In essence, CASA systems are "machine listening" systems that aim to separate mixtures of sound sources in the same way that human listeners do. CASA differs from the field of blind signal separation in that it is (at least to some extent) based on the mechanisms of the human auditory system, and thus uses no more than two microphone recordings of an acoustic environment. It is related to the cocktail party problem.

Contents 1 Applications 2 See also 3 External links 4 Further reading 5 References

[edit] Applications

Potentially, CASA technology can be applied in the following areas:

• Robust automatic speech recognition and speaker recognition in noisy environments
• Automatic transcription of musical audio recordings
• Hearing aids

[edit] See also

• auditory scene analysis
• machine vision
• blind signal separation
• cocktail party problem

[edit] External links

• Companion web site for Wang and Brown CASA book

[edit] Further reading

D. F. Rosenthal and H. G. Okuno (1998) Computational auditory scene analysis. Mahwah, NJ: Lawrence Erlbaum

[edit] References

1. ^ Wang, D. L. and Brown, G. J. (Eds.) (2006) Computational auditory scene analysis: Principles, algorithms and applications. IEEE Press/Wiley-Interscience