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StaffIncremental BloggerScalable Sound Sensing for People-Centric Mobile Phone Apps

Scalable Sound Sensing for People-Centric Mobile Phone Apps

Using the microphone on a cell phone,SoundSense software picks up sounds and automatically classifies sounds as “voice,” “music,” or “ambient noise.”

The architecture and algorithms are designed for scalability. SoundSense uses a combination of supervised and unsupervised learning techniques to classify both general sound types (e.g., music, voice) and discover novel sound events specific to individual users.

If a sound is repeated often enough or for long enough, SoundSense gives it a high “sound rank” and asks the user to confirm that it is significant and offers the option to label the sound.

SoundSense

Hong Lu, et al. SoundSense: Scalable Sound Sensing for People-Centric Applications on Mobile Phones, captured June 278, 2009.

Robert Heiny
Robert Heinyhttp://www.robertheiny.com
Robert W. Heiny, Ph.D. is a retired professor, social scientist, and business partner with previous academic appointments as a public school classroom teacher, senior faculty, or senior research member, and administrator. Appointments included at University of North Carolina at Chapel Hill, Peabody College and the Kennedy Center now of Vanderbilt University; and Brandeis University. Dr. Heiny also served as Director of the Montana Center on Disabilities. His peer reviewed contributions to education include publication in The Encyclopedia of Education (1971), and in professional journals and conferences. He served s an expert reviewer of proposals to USOE, and on a team that wrote plans for 12 state-wide and multistate special education and preschools programs. He currently writes user guides for educators and learners as well as columns for TuxReports.com.

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