Speech Separation by Humans and Machines

Description

   

The "~censored~-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 unravelling 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.


http://www.ftp2share.com/file/38749/Speech Separation by Humans and Machines.html

    thank you macworld

Disclaimer:
Contents of this page are indexed from the Internet. All actions are under your responsability. Email us to report illegal contents or external links and we'll remove them immediately.

Please check the description for download links if any or do a search to find alternative books.

Can't Download?
Please search mirrors if you can't find download links for "Speech Separation by Humans and Machines" in "Description" and someone else may update the links. Check the comments when back to find any updates.

Search Mirrors
Maybe some mirror pages will be helpful, search this book at top of this page or click here to find more info.

1. Ebooks list page : 605
2. Speech Separation by Humans and Machines
3. Speech.Separation.By.Humans.and.Machines
4. Speech Separation by Humans and Machines
5. [share_ebook] Humans, Animals, Machines: Blurring Boundaries Description: In the twenty-first century, the boundaries between both humans and machines and humans and animals are hotly contested and debated. In Humans, Animals, Machines, Glen A. Mazis exam
6. Blind Speech Separation
7. Humans, Animals, Machines: Blurring Boundaries
8. The Boundaries of Humanity: Humans, Animals, Machines
9. The Boundaries of Humanity: Humans, Animals, Machines
10. The Boundaries of Humanity: Humans, Animals, Machines (repost)
11. [share_ebook] Humans, Animals, Machines: Blurring Boundaries
12. Time-Domain Beamforming and Blind Source Separation: Speech Input in the Car Environment
13. [share_ebook] Time-Domain Beamforming and Blind Source Separation: Speech Input in the Car Environment
14. [share_ebook] Time-Domain Beamforming and Blind Source Separation: Speech Input in the Car Environment
15. [share_ebook] Humans, Animals, Machines: Blurring Boundaries
16. Hate Speech, Sex Speech, Free Speech