Robust speech filtering in impulsive noise environments

This thesis presents a new robust filtering technique that suppresses impulsive noise in speech signals. The method makes use of Projection Statistics based on medians to detect segments of speech with impulses. The autoregressive model employed to smooth out the speech signal is identified by means of a robust nonlinear estimator known as the Schweppe-type Huber GM-estimator. Simulation results are presented that demonstrate the effectiveness of the filter. Another contribution of the work is the development of a robust version of the Kalman filter based on the Huber M-estimator. The performances of this filter are evaluated for a simple autoregressive process.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Electrical and Computer Engineering

Department dc:contributor.department

Electrical and Computer Engineering

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

1999

Author dc:creator

• Ledoux, Christelle Michelle

Chair dc:contributor.committeechair

• Mili, Lamine M.

Committee members dc:contributor.committeemember

• Beex, A. A. Louis
• Reed, Jeffrey H.

• Linear Prediction Coding
• robust statistics
• speech processing

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Dc Identifier Other

etd-122099-142314

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/46325