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D. Ayllón, R. Gil-Pita, and M. Rosa-Zurera, "Computationally-Efficient Speech Enhancement Algorithm for Binaural Hearing Aids," Paper 9035, (2014 April.). doi: D. Ayllón, R. Gil-Pita, and M. Rosa-Zurera, "Computationally-Efficient Speech Enhancement Algorithm for Binaural Hearing Aids," Paper 9035, (2014 April.). doi:
Abstract: The improvement of speech intelligibility in hearing aids is a complex and unsolved problem. The recent development of binaural hearing aids allows the design of speech enhancement algorithms to take advantages of the benefits of binaural hearing. In this paper a novel source separation algorithm for binaural speech enhancement based on supervised machine learning and time-frequency masking is presented. The proposed algorithm requires less than 10% of the available instructions for signal processing in a state-of-the-art hearing aid and obtains good separation performance in terms of WDO for low SNR.

@article{ayllón2014computationally-efficient,
author={ayllón, david and gil-pita, roberto and rosa-zurera, manuel},
journal={journal of the audio engineering society},
title={computationally-efficient speech enhancement algorithm for binaural hearing aids},
year={2014},
volume={},
number={},
pages={},
doi={},
month={april},} @article{ayllón2014computationally-efficient,
author={ayllón, david and gil-pita, roberto and rosa-zurera, manuel},
journal={journal of the audio engineering society},
title={computationally-efficient speech enhancement algorithm for binaural hearing aids},
year={2014},
volume={},
number={},
pages={},
doi={},
month={april},
abstract={the improvement of speech intelligibility in hearing aids is a complex and unsolved problem. the recent development of binaural hearing aids allows the design of speech enhancement algorithms to take advantages of the benefits of binaural hearing. in this paper a novel source separation algorithm for binaural speech enhancement based on supervised machine learning and time-frequency masking is presented. the proposed algorithm requires less than 10% of the available instructions for signal processing in a state-of-the-art hearing aid and obtains good separation performance in terms of wdo for low snr.},}

TY - paper
TI - Computationally-Efficient Speech Enhancement Algorithm for Binaural Hearing Aids
SP - EP -
AU - Ayllón, David
AU - Gil-Pita, Roberto
AU - Rosa-Zurera, Manuel
PY - 2014
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - April 2014 TY - paper
TI - Computationally-Efficient Speech Enhancement Algorithm for Binaural Hearing Aids
SP - EP -
AU - Ayllón, David
AU - Gil-Pita, Roberto
AU - Rosa-Zurera, Manuel
PY - 2014
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - April 2014
AB - The improvement of speech intelligibility in hearing aids is a complex and unsolved problem. The recent development of binaural hearing aids allows the design of speech enhancement algorithms to take advantages of the benefits of binaural hearing. In this paper a novel source separation algorithm for binaural speech enhancement based on supervised machine learning and time-frequency masking is presented. The proposed algorithm requires less than 10% of the available instructions for signal processing in a state-of-the-art hearing aid and obtains good separation performance in terms of WDO for low SNR.