Human and machine hearing : extracting meaning from sound /

Human and machine hearing : extracting meaning from sound /

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Bibliographic Details
Author / Creator:Lyon, Richard F., author.
Imprint:Cambridge, United Kingdom ; New York, NY : Cambridge University Press, 2017.
©2017
Description:xxi, 567 pages, 8 unnumbered pages of plates : illustrations (some color) ; 27 cm
Language:English
Subject:
Hearing.
Auditory perception -- Mathematical models.
Auditory perception -- Computer simulation.
Auditory perception -- Computer simulation.
Auditory perception -- Mathematical models.
Hearing.
Format: Print Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/12700196
Hidden Bibliographic Details
ISBN:9781107007536
1107007534
Notes:Includes bibliographical references and indexes.
Summary:"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 claim, and to help engineers and scientists understand how the pieces fit together, so they can help move the art forward. There is still plenty to be done, and this book is my attempt to help focus the effort in this field into productive directions; to help new practitioners see enough of the evolution of ideas that they can skip to where new developments and experiments are needed, or to techniques that can already solve their sound understanding problems. The book-writing process has been tremendous fun, with support from family, friends, and colleagues. They do, however, have a tendency to ask two annoying questions: "Is the book done yet?" and "Who is your audience?" The first eventually answers itself, but I need to say a few words about the second. I find that interest in sound and hearing comes from people of many different disciplines, with complementary backgrounds and sometimes incompatible terminology and concepts. I want all of these people as my audience, as I want to teach a synthesis of their various viewpoints into a more comprehensive framework that includes everything needed to work on machine hearing problems. That is, electrical engineers, computer scientists, physicists, physiologists, audiologists, musicians, psychologists, and others are all part of my audience. Students, teachers, researchers, product managers, developers, and hackers are, too"--
Standard no.:13163099
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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