PERCEPTUALLY-BASED OBJECTIVE MEASURE FOR NON-INTRUSIVE SPEECH QUALITY ASSESSMENT

D. Picovici, A. E. Mahdi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper proposes a new perceptuallybased method for assessing speech quality and evaluates its performance. The method is based on comparing the received speech to an appropriate reference representing the closest match from a preformulated codebook. The codebook holds a number of optimally clustered speech parameter vectors extracted from a large number of various undistorted clean speech records. The objective auditory distances between vectors of the distorted speech signal and their corresponding matching references are then measured and appropriately converted into an equivalent subjective score. The optimal clustering of the reference codebook is achieved by using a dynamic k-means method. Efficient data mining technique known as Self-Organising Map is used to match the distorted speech vectors to the references. Speech parameters derived from Bark spectrum analysis, and Mel-Frequency Cepstral coefficients (MFCC) are used to provide speaker independent parametric representation of the speech signals as required by an output-based quality measure.

Original languageEnglish
Title of host publicationModels and Analysis of Vocal Emissions for Biomedical Applications, MAVEBA 2003
PublisherFirenze University Press
Pages169-172
Number of pages4
ISBN (Electronic)8884531551, 9788884531551
Publication statusPublished - 2003
Event3rd International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications, MAVEBA 2003 - Florence, Italy
Duration: 10 Dec 200312 Dec 2003

Publication series

NameModels and Analysis of Vocal Emissions for Biomedical Applications, MAVEBA 2003

Conference

Conference3rd International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications, MAVEBA 2003
Country/TerritoryItaly
CityFlorence
Period10/12/0312/12/03

Keywords

  • Perceptual Quality Measure
  • Perceptually-Based Speech Quality
  • Speech Processing

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