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T. Song, T. Qu, and J. Chen, "Multi-task Based Sound Localization Model," Paper 10366, (2020 May.). doi: T. Song, T. Qu, and J. Chen, "Multi-task Based Sound Localization Model," Paper 10366, (2020 May.). doi:
Abstract: For machine hearing in complex sences (i.e. reverberation, noise), sound localization either serves as the front-end or is implicitly encoded in speech enhancing models. However, it is suggested that there may be cross-talk between identification and localization streams in auditory system. Based on this idea, a multi-task based sound localization method is proposed in this study. The proposed model takes waveform as input, and simutaneously estimates the azimuth of sound source and the time-frequency (T-F) masks. Localization experiments were performed using binaural simulation in reverberant environment and the results show that comparing to single-task sound localization method, the presence of speech enhancement task can improve the localization performance.

@article{song2020multi-task,
author={song, tao and qu, tianshu and chen, jing},
journal={journal of the audio engineering society},
title={multi-task based sound localization model},
year={2020},
volume={},
number={},
pages={},
doi={},
month={may},} @article{song2020multi-task,
author={song, tao and qu, tianshu and chen, jing},
journal={journal of the audio engineering society},
title={multi-task based sound localization model},
year={2020},
volume={},
number={},
pages={},
doi={},
month={may},
abstract={for machine hearing in complex sences (i.e. reverberation, noise), sound localization either serves as the front-end or is implicitly encoded in speech enhancing models. however, it is suggested that there may be cross-talk between identification and localization streams in auditory system. based on this idea, a multi-task based sound localization method is proposed in this study. the proposed model takes waveform as input, and simutaneously estimates the azimuth of sound source and the time-frequency (t-f) masks. localization experiments were performed using binaural simulation in reverberant environment and the results show that comparing to single-task sound localization method, the presence of speech enhancement task can improve the localization performance.},}

TY - paper
TI - Multi-task Based Sound Localization Model
SP - EP -
AU - Song, Tao
AU - Qu, Tianshu
AU - Chen, Jing
PY - 2020
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - May 2020 TY - paper
TI - Multi-task Based Sound Localization Model
SP - EP -
AU - Song, Tao
AU - Qu, Tianshu
AU - Chen, Jing
PY - 2020
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - May 2020
AB - For machine hearing in complex sences (i.e. reverberation, noise), sound localization either serves as the front-end or is implicitly encoded in speech enhancing models. However, it is suggested that there may be cross-talk between identification and localization streams in auditory system. Based on this idea, a multi-task based sound localization method is proposed in this study. The proposed model takes waveform as input, and simutaneously estimates the azimuth of sound source and the time-frequency (T-F) masks. Localization experiments were performed using binaural simulation in reverberant environment and the results show that comparing to single-task sound localization method, the presence of speech enhancement task can improve the localization performance.