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.
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.
Authors:
Song, Tao; Qu, Tianshu; Chen, Jing
Affiliation:
Peking University
AES Convention:
148 (May 2020)
Paper Number:
10366
Publication Date:
May 28, 2020Import into BibTeX
Subject:
Posters: Perception
Permalink:
http://www.aes.org/e-lib/browse.cfm?elib=20783