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Human and machine hearing : extracting meaning from sound / Richard F. Lyon, Google, Inc.

"If we understood more about how humans hear, we could make machines hear better, in the sense of being able to analyze sound and extract useful and meaningful information from it. Or so I claim. I have been working for decades, but more intensely in recent years, to add some substance to this...

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Bibliographic Details
Main Author: Lyon, Richard F. (Author)
Format: Book
Language:English
Published: Cambridge, United Kingdom ; New York, NY : Cambridge University Press, 2017.
Subjects:
Hearing.
Auditory perception > Mathematical models.
Auditory perception > Computer simulation.
Auditory Perception > physiology.
Computer Simulation.
Models, Theoretical.
Table of Contents:
  • Theories of hearing
  • On logarithmic and power-law hearing
  • Human hearing overview
  • Acoustic approaches and auditory influence
  • Introduction to linear systems
  • Discrete-time and digital systems
  • Resonators
  • Gammatone and related filters
  • Nonlinear systems
  • Automatic gain control
  • Waves in distributed systems
  • Auditory filter models
  • Modeling the cochlea
  • The CARFAC digital cochlear model
  • The cascade of asymmetric resonators
  • The outer hair cell
  • The inner hair cell
  • The AGC loop filter
  • Auditory nerve and cochlear nucleus
  • The auditory image
  • Binaural spatial hearing
  • The auditory brain
  • Neural networks for machine learning
  • Feature spaces
  • Sound search
  • Musical melody matching
  • Other applications.

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