Fast communication: Perceptual evaluation of blind source separation for robust speech recognition

Authors:
Leandro Di Persia;Diego Milone;Hugo Leonardo Rufiner;Masuzo Yanagida
Affiliations:
Grupo de Investigación en Señales e Inteligencia Computacional, Facultad de Ingeniería y Ciencias Hídricas, Universidad Nacional del Litoral, Ciudad Universitaria, C.C. 217 Rut ...;Grupo de Investigación en Señales e Inteligencia Computacional, Facultad de Ingeniería y Ciencias Hídricas, Universidad Nacional del Litoral, Ciudad Universitaria, C.C. 217 Rut ...;Grupo de Investigación en Señales e Inteligencia Computacional, Facultad de Ingeniería y Ciencias Hídricas, Universidad Nacional del Litoral, Ciudad Universitaria, C.C. 217 Rut ...;Department of Intelligent Information Engineering and Science, Doshisha University, 1-3, Tatara-Miyakodani, Kyo-Tanabe 610-0321, Japan
Venue:
Signal Processing
Year:
2008

Citing 7
Cited 4

Fundamentals of speech recognition

Fundamentals of speech recognition
Objective quality evaluation in blind source separation for speech recognition in a real room

Signal Processing
Perceptual evaluation of speech quality (PESQ)-a new method for speech quality assessment of telephone networks and codecs

ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 200. on IEEE International Conference - Volume 02
Modeling perceptual similarity of audio signals for blind source separation evaluation

ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Performance measurement in blind audio source separation

IEEE Transactions on Audio, Speech, and Language Processing
Performance Estimation of Speech Recognition System Under Noise Conditions Using Objective Quality Measures and Artificial Voice

IEEE Transactions on Audio, Speech, and Language Processing
Evaluation of Objective Quality Measures for Speech Enhancement

IEEE Transactions on Audio, Speech, and Language Processing

Indeterminacy free frequency-domain blind separation of reverberant audio sources

IEEE Transactions on Audio, Speech, and Language Processing
Model-based expectation-maximization source separation and localization

IEEE Transactions on Audio, Speech, and Language Processing
Evaluating source separation algorithms with reverberant speech

IEEE Transactions on Audio, Speech, and Language Processing - Special issue on processing reverberant speech: methodologies and applications
Correlated Postfiltering and Mutual Information in Pseudoanechoic Model Based Blind Source Separation

Journal of Signal Processing Systems

Quantified Score

Hi-index	0.08

Visualization

Abstract

In a previous article, an evaluation of several objective quality measures as predictors of recognition rate after the application of a blind source separation algorithm was reported. In this work, the experiments were repeated using some new measures, based on the perceptual evaluation of speech quality (PESQ), which is part of the ITU P862 standard for evaluation of communication systems. The raw PESQ and a nonlinearly transformed PESQ were evaluated, together with several composite measures. The results show that the PESQ-based measures outperformed all the measures reported in the previous work. Based on these results, we recommend the use of PESQ-based measures to evaluate blind source separation algorithms for automatic speech recognition.