Research on Improved Conv-TasNet of Speech Enhancement for Non-Stationary and Low SNR Noise During Aircraft Operating

Deyin Zhang, Wenxuan Hong, Juntong Li, Yuyao Zhang, Li Wang

2022

Abstract

A speech enhancement method based on improved Conv-TasNet (Convolution Time-Domain Audio Separation Network) is proposed in this paper so as to solve the problems of the high noise environment of the airport seriously affects the communication between airport ground staff. The traditional speech enhancement algorithm used by civil aviation is not effective in suppressing low SNR (signal-to-noise) ratio and non-stationary noise. The improved Conv-TasNet is based on the baseline Conv-TasNet, and fused the multi-head-attention module and the Efficient Channel Attention Network channel attention module. The ablation experiment is carried out by using four neural networks to deal with the noisy speech of five kinds SNR: 10dB, 5dB, 0dB, -5dB respectively. The performance of the neural network is analyzed by four subjective and objective speech evaluation indicators including MOS (Mean Opinion Score), segSNR (Segment Signal-to-Noise Ratio), PESQ (Perceptual Evaluation of Speech Quality) and STOI (Short-Time Objective Intelligibility). The experiment results show that, the improved Conv-TasNet has an average increase of 1.4984 in MOS, 11.9261 in segSNR, 0.5868 in PESQ, and 0.0455 in STOI compared with the baseline Conv-TasNet. The improved neural network has better speech quality and intelligibility, which can solve the problem of used in baseline Conv-TasNet has poor effect on speech enhancement with low SNR and non-stationary environmental noise during aircraft operating.

Paper Citation

in Harvard Style

Zhang D., Hong W., Li J., Zhang Y. and Wang L. (2022). Research on Improved Conv-TasNet of Speech Enhancement for Non-Stationary and Low SNR Noise During Aircraft Operating. In Proceedings of the 3rd International Symposium on Automation, Information and Computing - Volume 1: ISAIC; ISBN 978-989-758-622-4, SciTePress, pages 776-781. DOI: 10.5220/0012047300003612

in Bibtex Style

@conference{isaic22,
author={Deyin Zhang and Wenxuan Hong and Juntong Li and Yuyao Zhang and Li Wang},
title={Research on Improved Conv-TasNet of Speech Enhancement for Non-Stationary and Low SNR Noise During Aircraft Operating},
booktitle={Proceedings of the 3rd International Symposium on Automation, Information and Computing - Volume 1: ISAIC},
year={2022},
pages={776-781},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012047300003612},
isbn={978-989-758-622-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Symposium on Automation, Information and Computing - Volume 1: ISAIC
TI - Research on Improved Conv-TasNet of Speech Enhancement for Non-Stationary and Low SNR Noise During Aircraft Operating
SN - 978-989-758-622-4
AU - Zhang D.
AU - Hong W.
AU - Li J.
AU - Zhang Y.
AU - Wang L.
PY - 2022
SP - 776
EP - 781
DO - 10.5220/0012047300003612
PB - SciTePress