Improving the quality of speech in noisy environments

In this thesis, we are interested in processing noisy speech signals that are meant to be heard by humans, and hence we approach the noise-suppression problem from a perceptual perspective. We develop a noise-suppression paradigm that is based on a model of the human auditory system, where we process signals in a way that is natural to the human ear. Under this paradigm, we transform an audio signal in to a perceptual domain, and processes the signal in this perceptual domain. This approach allows us to reduce the background noise and the audible artifacts that are seen in traditional noise-suppression algorithms, while preserving the quality of the processed speech. We develop a single- and dual-microphone algorithm based on this perceptual paradigm, and conduct subjecting tests to show that this approach outperforms traditional noise-suppression techniques. Moreover, we investigate the cause of audible artifacts that are generated as a result of suppressing the noise in noisy signals, and introduce constraints on the noise-suppression gain such that these artifacts are reduced.

Department dc:contributor.department

Electrical and Computer Engineering

Grantor dc:publisher

Georgia Institute of Technology

Year dc:date.issued

2012

Author dc:creator

• Parikh, Devi

Advisor dc:contributor.advisor

• Anderson, David V.

Committee members dc:contributor.committeemember

• Bhatti, Pamela T.
• Clements, Mark A.
• McClellan, James H.
• Vidakovic, Branislav

• Blind source separation
• Perceptual processing
• Noise suppression
• Speech processing

Handle dc:identifier.uri

http://hdl.handle.net/1853/45889

OAI identifier oai:identifier

oai:repository.gatech.edu:1853/45889