机读格式显示(MARC)
- 000 03979cam a2200373 i 4500
- 008 160916s2017 enkaf b 001 0 eng c
- 020 __ |a 9781107007536 |q hardback |q alkaline paper
- 040 __ |a OU/DLC |b eng |e rda |c OSU |d DLC |d BTCTA |d OCLCF |d NUI |d YDX |d YDX |d OCLCO |d OBE
- 050 00 |a QP461 |b .L96 2017
- 082 00 |a 612.8/50113 |2 23
- 099 __ |a CAL 022017098529
- 100 1_ |a Lyon, Richard F., |e author.
- 245 10 |a Human and machine hearing : |b extracting meaning from sound / |c Richard F. Lyon, Google, Inc.
- 264 _1 |a Cambridge, United Kingdom ; |a New York, NY, USA : |b Cambridge University Press, |c 2017.
- 300 __ |a xxi, 567 pages, 8 unnumbered pages of plates : |b illustrations (some color) ; |c 27 cm
- 336 __ |a text |b txt |2 rdacontent
- 337 __ |a unmediated |b n |2 rdamedia
- 338 __ |a volume |b nc |2 rdacarrier
- 504 __ |a Includes bibliographical references (pages 497-543) and indexes.
- 505 0_ |a Part I. Sound analysis and representation overview. Introduction -- Theories of hearing -- On logarithmic and power-law hearing -- Human hearing overview -- Acoustic approaches and auditory influence -- Part II. Systems theory for hearing. Introduction to linear systems -- Discrete-time and digital systems -- Resonators -- Gammatone and related filters -- Nonlinear systems -- Automatic gain control -- Waves in distributed systems -- Part III. The auditory periphery. 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 -- Part IV. The auditory nervous system. Auditory nerve and cochlear nucleus -- The auditory image -- Binaural spatial hearing -- The auditory brain -- Part V. Learning and applications. Neural networks for machine learning -- Feature spaces -- Sound search -- Musical melody matching -- Other applications.
- 520 __ |a "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"--Provided by publisher.
- 650 _0 |a Auditory perception |x Mathematical models.
- 650 _0 |a Auditory perception |x Computer simulation.