The NPU-Elevoc Personalized Speech Enhancement System for Icassp2023 DNS Challenge

Xiaopeng Yan, Yindi Yang, Zhihao Guo, Liangliang Peng, Lei Xie

Research output: Contribution to journalConference articlepeer-review

5 Scopus citations

Abstract

This paper describes our NPU-Elevoc personalized speech enhancement system (NAPSE) for the 5th Deep Noise Suppression Challenge[1] at ICASSP 2023. Based on the superior two-stage model TEA-PSE 2.0 [2], our system particularly explores better strategy for speaker embedding fusion, optimizes the model training pipeline, and leverages adversarial training and multi-scale loss. According to the results12, our system is tied for the 1st place in the headset track (track 1) and ranked 2nd in the speakerphone track (track 2).

Keywords

  • deep learning
  • generative adversarial network
  • personalized speech enhancement
  • real-time

Fingerprint

Dive into the research topics of 'The NPU-Elevoc Personalized Speech Enhancement System for Icassp2023 DNS Challenge'. Together they form a unique fingerprint.

Cite this