The NPU-Elevoc Personalized Speech Enhancement System for ICASSP2023 DNS Challenge
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Abstract (arXiv)
This paper describes our NPU-Elevoc personalized speech enhancement system (NAPSE) for the 5th Deep Noise Suppression Challenge at ICASSP 2023. Based on the superior two-stage model TEA-PSE 2.0, 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 results, our system is tied for the 1st place in the headset track (track 1) and ranked 2nd in the speakerphone track (track 2).
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 13 Mar 2023.
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Citing papers per year: 2024: 1; 2025: 2; 2026: 1.
4 papers.
- 2025LLaSE-G1: Incentivizing Generalization Capability for LLaMA-based Speech Enhancementcited by 19
- 2025High-Fidelity Speech Enhancement via Discrete Audio Tokenscited by 2
- 2024Personalized Speech Enhancement Without a Separate Speaker Embedding Modelcited by 1
- 2026Post-Training Speech Enhancement Language Models with Perceptual Rewardscited by 1
- 2026Post-Training Speech Enhancement Language Models with Perceptual Rewards19 Jun 2026
- 2025High-Fidelity Speech Enhancement via Discrete Audio Tokens2 Oct 2025
- 2025LLaSE-G1: Incentivizing Generalization Capability for LLaMA-based Speech Enhancement1 Mar 2025
- 2024Personalized Speech Enhancement Without a Separate Speaker Embedding Model14 Jun 2024