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Human and Machine Hearing
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  • Cited by 9
  • Cited by
    This book has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Ogiela, Marek R. and Ogiela, Lidia 2019. Innovative Mobile and Internet Services in Ubiquitous Computing. Vol. 773, Issue. , p. 432.

    Wang, DeLiang and Chen, Jitong 2018. Supervised Speech Separation Based on Deep Learning: An Overview. IEEE/ACM Transactions on Audio, Speech, and Language Processing, Vol. 26, Issue. 10, p. 1702.

    Dorfan, Yuval Plinge, Axel Hazan, Gershon and Gannot, Sharon 2018. Distributed Expectation-Maximization Algorithm for Speaker Localization in Reverberant Environments. IEEE/ACM Transactions on Audio, Speech, and Language Processing, Vol. 26, Issue. 3, p. 682.

    Xu, Ying Thakur, Chetan S. Singh, Ram K. Hamilton, Tara Julia Wang, Runchun M. and van Schaik, André 2018. A FPGA Implementation of the CAR-FAC Cochlear Model. Frontiers in Neuroscience, Vol. 12, Issue. ,

    Bell, Andrew and Wit, Hero P. 2018. Cochlear impulse responses resolved into sets of gammatones: the case for beating of closely spaced local resonances. PeerJ, Vol. 6, Issue. , p. e6016.

    Singh, Ram Kuber Xu, Ying Wang, Runchun Hamilton, Tara Julia van Schaik, Andre and Denham, Susan L. 2018. CAR-Lite: A Multi-Rate Cochlea Model on FPGA. p. 1.

    Xu, Ying Afshar, Saeed Singh, Ram Kuber Hamilton, Tara Julia Wang, Runchun and van Schaik, Andre 2018. A Machine Hearing System for Binaural Sound Localization based on Instantaneous Correlation. p. 1.

    Demertzis, Konstantinos Iliadis, Lazaros S. and Anezakis, Vardis-Dimitris 2018. Extreme deep learning in biosecurity: the case of machine hearing for marine species identification. Journal of Information and Telecommunication, Vol. 2, Issue. 4, p. 492.

    Ogiela, Marek R. Ogiela, Lidia D. Iftekharuddin, Khan M. Awwal, Abdul A. S. Márquez, Andrés García Vázquez, Mireya and Diaz-Ramirez, Víctor H. 2017. Cognitive approaches for patterns analysis and security applications. p. 25.

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Book description

Human and Machine Hearing is the first book to comprehensively describe how human hearing works and how to build machines to analyze sounds in the same way that people do. Drawing on over thirty-five years of experience in analyzing hearing and building systems, Richard F. Lyon explains how we can now build machines with close-to-human abilities in speech, music, and other sound-understanding domains. He explains human hearing in terms of engineering concepts, and describes how to incorporate those concepts into machines for a wide range of modern applications. The details of this approach are presented at an accessible level, to bring a diverse range of readers, from neuroscience to engineering, to a common technical understanding. The description of hearing as signal-processing algorithms is supported by corresponding open-source code, for which the book serves as motivating documentation.

Reviews

‘Lyon is a great teacher and he has a deep understanding of the science and art of machine hearing. The reader will be greatly rewarded for engaging with any and all sections of the book.'

Roy D. Patterson - University of Cambridge, from the Foreword

'If you want to read an engaging and informative history of the study of hearing and you want to learn about the science of hearing, you should read Human and Machine Hearing. If you want to build a hearing 'machine,' you must read Human and Machine Hearing.'

William Yost - Arizona State University and best-selling author of Fundamentals of Hearing: An Introduction

'This is a wonderfully written and much-needed book, written by a true world-class expert in the field. It is an ideal reference for students and professional researchers alike - authoritative and delightfully readable. It provides the best and most up-to-date coverage of auditory neuroscience and modeling there is.'

Daniel J. Levitin - best-selling author of This Is Your Brain on Music

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