TEA-PSE: Tencent-Ethereal-Audio-Lab Personalized Speech Enhancement System for ICASSP 2022 DNS Challenge
By Yukai Ju, Wei Rao, Xiaopeng Yan, Yihui Fu, Shubo Lv, Luyao Cheng, Yannan Wang, Linfu Xie, Shidong Shang. 2022
55 citations recorded by the source corpus.
This paper describes Tencent Ethereal Audio Lab – Northwestern Polytechnical University personalized speech enhancement (TEA-PSE) system submitted to track 2 of the ICASSP 2022 Deep Noise Suppression (DNS) challenge. Our system specifically combines the dual-stage network which is a superior real-time speech enhancement framework with the ECAPA-TDNN speaker embedding network which achieves state-of-the-art performance in speaker verification. The dual-stage network aims to decouple the primal speech enhancement problem into multiple easier sub-problems. Specifically, in stage 1, only the magnitude of the target speech is estimated, which is incorporated with the noisy phase to obtain a coarse complex spectrum estimation. To facilitate the formal estimation, in stage 2, an auxiliary network serves as a post-processing module, where residual noise and interfering speech are further suppressed and the phase information is effectively modified. With the asymmetric loss function to penalize over-suppression, more target speech is preserved, which is helpful for both speech recognition performance and subjective sense of hearing. Our system reaches 3.97 in overall audio quality (OVRL) MOS and 0.69 in word accuracy (WAcc) on the blind test set of the challenge, which outperforms the DNS baseline by 0.57 OVRL and ranks 1st in track 2.
Subfields: Artificial Intelligence, Signal Processing
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Ross Cutler
- Vishak Gopal
- Sebastian Braun
- Chandan K. A. Reddy
- Robert Aichner
- Harishchandra Dubey
- Hannes Gamper
- Sriram Srinivasan
In Signal Processing
- Ross Cutler
- Vishak Gopal
- Chandan K. A. Reddy
- Robert Aichner
- Hannes Gamper
- Sebastian Braun
- Harishchandra Dubey
- Sriram Srinivasan
Citations in the corpus
- Icassp 2022 Deep Noise Suppression Challenge (2022, background): “The performance of the personalized DNS track also show excellent performance, greatly exceeding results of our first personalized DNS challenge [2] with the winner [27] providing very good dOVRL with low dSIG and low dWAcc.”