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.