Speech Separation by Humans and Machines
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The "cocktail-party effect" - the ability to focus on one voice in a sea of noises - is a highly sophisticated skill that is usually effortless to listeners but largely impossible for machines. Investigating and unraveling this capacity spans numerous fields including psychology, physiology, engineering, and computer science. All these perspectives are brought together in this volume which, for the first time, provides a comprehensive and authoritative discussion of our understanding of how humans separate speech, and the state of the art in approaching these abilities with machines.This material is drawn from an October 2003 workshop, sponsored by the National Science Foundation, on speech separation. Leading authorities from around the world were invited to present their perspectives and discuss the points of contact to other perspectives. The result is a clear and uniform overview of this problem, and a primer in what is emerging as an important, active and successful area for the development of new techniques and applications. Chapters include historical and current summaries of relevant research in behavioral science, neuroscience and engineering, along with more in-depth descriptions of several of the most exciting current research projects and techniques, including the latest experimental results illuminating how listeners organize the mixtures of sound they hear, and the most powerful and successful signal processing and machine learning techniques for the separation of real-world recordings of sound mixtures by one or more microphones.There is no comparable collection that seeks to bring together the underlying experimental science and the wide variety of technical approaches to give an integrated picture of the problem and solutions to speech separation. Those specializing in speech science, hearing science, neuroscience, or computer science and engineers working on applications such as automatic speech recognition, cochlear implants, hands-free telephones, sound recording, multimedia indexing and retrieval will find Speech Separation by Humans and Machines a useful and inspiring read.
ForewordPrefaceSpeech segregation : problems and perspectives1Auditory scene analysis : examining the role of nonlinguistic auditory processing in speech perception5Speech separation : further insights from recordings of event-related brain potentials in humans13Recurrent timing nets for F0-based speaker separation31Blind source separation using graphical models55Speech recognizer based maximum likelihood beamforming65Exploiting redundancy to construct listening systems83Automatic speech processing by inference in generative models97Signal separation motivated by human auditory perception : applications to automatic speech recognition135Speech segregation using an event-synchronous auditory image and STRAIGHT155Underlying principles of a high-quality speech manipulation system STRAIGHT and its application to speech segregation167On ideal binary mask as the computational goal of auditory scene analysis181The history and future of CASA199Techniques for robust speech recognition in noisy and reverberant conditions213Source separation, localization, and comprehension in humans, machines, and human-machine systems221The cancellation principle in acoustic scene analysis245Informational and energetic masking effects in multitalker speech perception261Masking the feature information in multi-stream speech-analogue displays269Interplay between visual and audio scene analysis283Evaluating speech separation systems295Making sense of everyday speech : a glimpsing account305
