Date of Publication

12-2003

Document Type

Master's Thesis

Degree Name

Master of Science in Electronics and Communications Engineering

Subject Categories

Electrical and Computer Engineering | Electrical and Electronics

College

Gokongwei College of Engineering

Department/Unit

Electronics and Communications Engineering

Thesis Adviser

Edwin Sybingco

Defense Panel Chair

Felicito S. Caluyo

Defense Panel Member

Felixberto Cruz
Virgilio Conanan

Abstract/Summary

Blind source separation aims to recover or estimate statistically independent speech source signals that have been mixed. The combiner characteristics and the propagation channel are not known, thus the term blind. There are many solutions to blind source separation. Output decorrelation method as the separation croterion is one of the simplest, yet effective solutions. This paper describes a new model for the output decorrelation method by introducing an extra sensor measurement in the demixing section. The classical 2-source x 2-sensor model is modified to a 2-source x 3-sensor model to improve separation behavior. Derived equations for the 2x3 model show an increase in the complexity of the solution of the demixing coefficients, however, performance tests, both objective and subjective, are utilized to gauge the behavior of both models and show an improved separation behavior by as much as an increase in a rating of 1.5 in a scale of 1 to 5.

Abstract Format

html

Note

Title from title screen.

Language

English

Format

Electronic

Accession Number

CDTG003591

Shelf Location

Archives, The Learning Commons, 12F Henry Sy Sr. Hall

Physical Description

1 computer optical disc ; 4 3/4 in.

Keywords

Speech processing systems; Signal processing; Detectors; Simulation methods

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