This paper introduces the Unbeatable Team's submission to the ICASSP 2023 Deep Noise Suppression (DNS) Challenge. We expand our previous work, TEA-PSE, to its upgraded version -- TEA-PSE 3.0. Specifically, TEA-PSE 3.0 incorporates a residual LSTM after squeezed temporal convolution network (S-TCN) to enhance sequence modeling capabilities. Additionally, the local-global representation (LGR) structure is introduced to boost speaker information extraction, and multi-STFT resolution loss is used to effectively capture the time-frequency characteristics of the speech signals. Moreover, retraining methods are employed based on the freeze training strategy to fine-tune the system. According to the official results, TEA-PSE 3.0 ranks 1st in both ICASSP 2023 DNS-Challenge track 1 and track 2.

翻译：本文介绍了Unbeatable团队在ICASSP 2023深度噪声抑制（DNS）挑战赛中的参赛方案。我们在前期工作TEA-PSE的基础上，将其升级为增强版本——TEA-PSE 3.0。具体而言，TEA-PSE 3.0在压缩时序卷积网络（S-TCN）之后引入残差长短时记忆网络（LSTM），以增强序列建模能力。此外，引入局部-全局表征（LGR）结构以提升说话人信息提取能力，并采用多STFT分辨率损失函数以有效捕获语音信号的时频特性。同时，基于冻结训练策略的重训练方法被用于对系统进行微调。根据官方结果，TEA-PSE 3.0在ICASSP 2023 DNS挑战赛赛道一和赛道二中均位列第一。