Low complexity speech enhancement network based on frame-level Swin transformer
W Jiang, C Sun, F Chen, Y Leng, Q Guo, J Sun, J Peng - Electronics, 2023 - mdpi.com
In recent years, Transformer has shown great performance in speech enhancement by
applying multi-head self-attention to capture long-term dependencies effectively. However …
applying multi-head self-attention to capture long-term dependencies effectively. However …
[HTML][HTML] 基于超轻量通道注意力的端对端语音增强方法
洪依， 孙成立， 冷严 - 智能科学与技术学报, 2021 - infocomm-journal.com
摘要全卷积时域音频分离网络(Conv-TasNet) 是近年提出的一种主流的端对端语音分离模型.
Conv-TasNet 利用膨胀卷积扩大感受野, 使其在空间上可以融合更多语音特征 …
Conv-TasNet 利用膨胀卷积扩大感受野, 使其在空间上可以融合更多语音特征 …
[PDF][PDF] CROWD SPEAKER IDENTIFICATION METHODOLOGIES, DATASETS AND FEATURES
GQ Ali, HA Abdulmohsin - Journal of Applied Engineering and …, 2024 - researchgate.net
Crowded speech or Overlapping speech, occurs when multiple individuals speak
simultaneously, which is a common occurrence in real-life scenarios such as telephone …
simultaneously, which is a common occurrence in real-life scenarios such as telephone …