Computational Auditory Scene Analysis:Principles, Algorithms, and Applications

Cover Image Copyright Year: 2006
Author(s): DeLiang Wang; Guy J. Brown
Book Type: Wiley-IEEE Press
Content Type : Books
Topics: Communication, Networking & Broadcasting ;  Components, Circuits, Devices & Systems ;  Computing & Processing ;  Signal Processing & Analysis
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Abstract

How can we engineer systems capable of "cocktail party" listening?

Human listeners are able to perceptually segregate one sound source from an acoustic mixture, such as a single voice from a mixture of other voices and music at a busy cocktail party. How can we engineer "machine listening" systems that achieve this perceptual feat?

Albert Bregman's book Auditory Scene Analysis, published in 1990, drew an analogy between the perception of auditory scenes and visual scenes, and described a coherent framework for understanding the perceptual organization of sound. His account has stimulated much interest in computational studies of hearing. Such studies are motivated in part by the demand for practical sound separation systems, which have many applications including noise-robust automatic speech recognition, hearing prostheses, and automatic music transcription. This emerging field has become known as computational auditory scene analysis (CASA).

Computational Auditory Scene A alysis: Principles, Algorithms, and Applications provides a comprehensive and coherent account of the state of the art in CASA, in terms of the underlying principles, the algorithms and system architectures that are employed, and the potential applications of this exciting new technology. With a Foreword by Bregman, its chapters are written by leading researchers and cover a wide range of topics including:

  • Estimation of multiple fundamental frequencies
  • Feature-based and model-based approaches to CASA
  • Sound separation based on spatial location
  • Processing for reverberant environments
  • Segregation of speech and musical signals
  • Automatic speech recognition in noisy environments
  • Neural and perceptual modeling of auditory organization

The text is written at a level that will be accessible to graduate students and researchers from related science and engineering disciplines. The extensive bibliography accompanying each hapter will also make this book a valuable reference source. A web site accompanying the text (www.casabook.org) features software tools and sound demonstrations.

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    Contributors

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    Acronyms

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    Fundamentals of Computational Auditory Scene Analysis

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    This chapter contains sections titled:

  • Human Auditory Scene Analysis

  • Computational Auditory Scene Analysis (CASA)

  • Basics of CASA Systems

  • CASA Evaluation

  • Other Sound Separation Approaches

  • A Brief History of CASA (Prior to 2000)

  • Conclusions

  • This chapter contains sections titled:

  • Acknowledgments

  • References

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    Multiple F0 Estimation

    Computational Auditory Scene Analysis:Principles, Algorithms, and Applications
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    This chapter contains sections titled:

  • Introduction

  • Signal Models

  • Single-Voice F0 Estimation

  • Multiple-Voice F0 Estimation

  • Issues

  • Other Sources of Information

  • Estimating the Number of Sources

  • Evaluation

  • Application Scenarios

  • Conclusion

  • This chapter contains sections titled:

  • Acknowledgments

  • References

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    FeatureBased Speech Segregation

    Computational Auditory Scene Analysis:Principles, Algorithms, and Applications
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    This chapter contains sections titled:

  • Introduction

  • Feature Extraction

  • Auditory Segmentation

  • Simultaneous Grouping

  • Sequential Grouping

  • Discussion

  • This chapter contains sections titled:

  • Acknowledgments

  • References

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    ModelBased Scene Analysis

    Computational Auditory Scene Analysis:Principles, Algorithms, and Applications
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    This chapter contains sections titled:

  • Introduction

  • Source Separation as Inference

  • Hidden Markov Models

  • Aspects of Model-Based Systems

  • Discussion

  • Conclusions

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  • References

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    Binaural Sound Localization

    Computational Auditory Scene Analysis:Principles, Algorithms, and Applications
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    This chapter contains sections titled:

  • Introduction

  • Physical and Physiological Mechanisms Underlying Auditory Localization

  • Spatial Perception of Single Sources

  • Spatial Perception of Multiple Sources

  • Models of Binaural Perception

  • Multisource Sound Localization

  • General Discussion

  • This chapter contains sections titled:

  • Acknowledgments

  • References

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    LocalizationBased Grouping

    Computational Auditory Scene Analysis:Principles, Algorithms, and Applications
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    This chapter contains sections titled:

  • Introduction

  • Classical Beamforming Techniques

  • Location-Based Grouping Using Interaural Time Difference Cue

  • Location-Based Grouping Using Interaural Intensity Difference Cue

  • Location-Based Grouping Using Multiple Binaural Cues

  • Discussion and Conclusions

  • This chapter contains sections titled:

  • Acknowledgments

  • References

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    Reverberation

    Computational Auditory Scene Analysis:Principles, Algorithms, and Applications
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    This chapter contains sections titled:

  • Introduction

  • Effects of Reverberation on Listeners

  • Effects of Reverberation on Machines

  • Mechanisms Underlying Robustness to Reverberation in Human Listeners

  • Reverberation-Robust Acoustic Processing

  • CASA and Reverberation

  • Discussion and Conclusions

  • This chapter contains sections titled:

  • Acknowledgments

  • References

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    Analysis of Musical Audio Signals

    Computational Auditory Scene Analysis:Principles, Algorithms, and Applications
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    This chapter contains sections titled:

  • Introduction

  • Music Scene Description

  • Estimating Melody and Bass Lines

  • Estimating Beat Structure

  • Estimating Chorus Sections and Repeated Sections

  • Discussion and Conclusions

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  • References

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    Robust Automatic Speech Recognition

    Computational Auditory Scene Analysis:Principles, Algorithms, and Applications
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    This chapter contains sections titled:

  • Introduction

  • ASA and Speech Perception in Humans

  • Speech Recognition by Machine

  • Primitive CASA and ASR

  • Model-Based CASA and ASR

  • Discussion and Conclusions

  • Concluding Remarks

  • This chapter contains sections titled:

  • References

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    Neural and Perceptual Modeling

    Computational Auditory Scene Analysis:Principles, Algorithms, and Applications
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    This chapter contains sections titled:

  • Introduction

  • The Neural Basis of Auditory Grouping

  • Models of Individual Neurons

  • Models of Specific Perceptual Phenomena

  • The Oscillatory Correlation Framework for CASA

  • Schema-Driven Grouping

  • Discussion

  • This chapter contains sections titled:

  • Acknowledgments

  • References

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    Index

    Computational Auditory Scene Analysis:Principles, Algorithms, and Applications
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