Open Access
A Speech Processing Research Platform for Android Based Smart Phones and Tablets
Roger Chappel,Kuldip K. Paliwal +1 more
- 01 Jan 2012
- Vol. 54, Iss: 2
TL;DR: In this paper, a new research and education platform for speech processing called Speech Enhancement for Android (SEA) is presented, which incorporates past and present speech enhancement techniques applied to recorded speech corrupted by real world noise sources.
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Abstract: This paper presents a new research and education platform for speech processing. The platform is called Speech Enhancement for Android (SEA) and incorporates past and present speech enhancement techniques applied to recorded speech corrupted by real world noise sources. Researchers, students and teaching staff can use this platform to perform speech enhancement and observe its effects on the linguistic content of speech. This paper outlines the speech processing strategies implemented in SEA along with discussing the benefits of this new interactive method to present speech processing theory and research. Index Terms: speech enhancement, speech processing, spectrogram, Android, smart phone
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References
Suppression of acoustic noise in speech using spectral subtraction
TL;DR: A stand-alone noise suppression algorithm that resynthesizes a speech waveform and can be used as a pre-processor to narrow-band voice communications systems, speech recognition systems, or speaker authentication systems.
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•Book
Extrapolation, Interpolation, and Smoothing of Stationary Time Series
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- 01 Mar 1964
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