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D. Ayllon, R. Gil Pita, and M. Rosa-Zurera, "Estimation of the Probability Density Function of the Interaural Level Diferences for Binaural Speech Separation," Paper 8273, (2010 November.). doi: D. Ayllon, R. Gil Pita, and M. Rosa-Zurera, "Estimation of the Probability Density Function of the Interaural Level Diferences for Binaural Speech Separation," Paper 8273, (2010 November.). doi:
Abstract: Source separation techniques are applied to audio signals to separate several sources from one mixture. One important challenge of speech processing is noise suppression and several methods have been proposed. However, in some applications like hearing aids, we are not interested just in removing noise from speech but amplifying speech and attenuating noise. A novel method based on the estimation of the Power Density Function of the Interaural Level Differences in conjunction with time-frequency decomposition and binary masking is applied to speech-noise mixtures in order to obtain both signals separately. Results show how both signal are clearly separated and the method entails low computational cost, so it could be implemented in a real-time environment, such as a hearing aid device.

@article{ayllon2010estimation,
author={ayllon, david and gil pita, roberto and rosa-zurera, manuel},
journal={journal of the audio engineering society},
title={estimation of the probability density function of the interaural level diferences for binaural speech separation},
year={2010},
volume={},
number={},
pages={},
doi={},
month={november},} @article{ayllon2010estimation,
author={ayllon, david and gil pita, roberto and rosa-zurera, manuel},
journal={journal of the audio engineering society},
title={estimation of the probability density function of the interaural level diferences for binaural speech separation},
year={2010},
volume={},
number={},
pages={},
doi={},
month={november},
abstract={source separation techniques are applied to audio signals to separate several sources from one mixture. one important challenge of speech processing is noise suppression and several methods have been proposed. however, in some applications like hearing aids, we are not interested just in removing noise from speech but amplifying speech and attenuating noise. a novel method based on the estimation of the power density function of the interaural level differences in conjunction with time-frequency decomposition and binary masking is applied to speech-noise mixtures in order to obtain both signals separately. results show how both signal are clearly separated and the method entails low computational cost, so it could be implemented in a real-time environment, such as a hearing aid device.},}

TY - paper
TI - Estimation of the Probability Density Function of the Interaural Level Diferences for Binaural Speech Separation
SP - EP -
AU - Ayllon, David
AU - Gil Pita, Roberto
AU - Rosa-Zurera, Manuel
PY - 2010
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - November 2010 TY - paper
TI - Estimation of the Probability Density Function of the Interaural Level Diferences for Binaural Speech Separation
SP - EP -
AU - Ayllon, David
AU - Gil Pita, Roberto
AU - Rosa-Zurera, Manuel
PY - 2010
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - November 2010
AB - Source separation techniques are applied to audio signals to separate several sources from one mixture. One important challenge of speech processing is noise suppression and several methods have been proposed. However, in some applications like hearing aids, we are not interested just in removing noise from speech but amplifying speech and attenuating noise. A novel method based on the estimation of the Power Density Function of the Interaural Level Differences in conjunction with time-frequency decomposition and binary masking is applied to speech-noise mixtures in order to obtain both signals separately. Results show how both signal are clearly separated and the method entails low computational cost, so it could be implemented in a real-time environment, such as a hearing aid device.