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 experimental science 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.
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