Human and Machine Hearing

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Cambridge University Press, May 2, 2017 - Computers - 567 pages
"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"--
 

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Contents

Sound Analysis and Representation Overview
1
Theories of Hearing
23
On Logarithmic and PowerLaw Hearing
33
Human Hearing Overview
46
Acoustic Approaches and Auditory Influence
78
Systems Theory for Hearing
95
DiscreteTime and Digital Systems
126
Resonators
145
The Outer Hair Cell
309
The Inner Hair Cell
320
The AGC Loop Filter
331
The Auditory Nervous System
345
The Auditory Image
355
Binaural Spatial Hearing
379
The Auditory Brain
400
Learning and Applications
417

Gammatone and Related Filters
169
Nonlinear Systems
189
Automatic Gain Control
202
Waves in Distributed Systems
219
The Auditory Periphery
237
Modeling the Cochlea
265
The CARFAC Digital Cochlear Model
293
The Cascade of Asymmetric Resonators
299
Feature Spaces
441
Sound Search
450
Musical Melody Matching
467
Other Applications
481
Bibliography
497
Author Index
545
Subject Index
557
Copyright

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About the author (2017)

Richard F. Lyon leads Google's research and applications development in machine hearing as well as the team that developed camera systems for the Google Street View project. He is an engineer and scientist known for his work on cochlear models and auditory correlograms for the analysis and visualization of sound, and for implementations of these models, which he has also worked on at Xerox PARC, Schlumberger, and Apple. Lyon is a Fellow of the Institute of Electrical and Electronics Engineers and of the Association for Computing Machinery, and is among the world's top 500 editors of Wikipedia. He has published widely in hearing, VLSI design, signal processing, speech recognition, computer architecture, photographic technology, handwriting recognition, computer graphics, and slide rules. He holds 58 issued United States patents for his inventions, including the optical mouse.

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