# The NPU-Elevoc Personalized Speech Enhancement System for ICASSP2023 DNS Challenge

arXiv: https://arxiv.org/abs/2303.06811 · HTML: https://mlsanity.com/paper/2303.06811/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Mar 2023.

## Built on by (most cited first, 4 of 4)

- [LLaSE-G1: Incentivizing Generalization Capability for LLaMA-based Speech Enhancement](https://mlsanity.com/paper/2503.00493/) (2025)
- [High-Fidelity Speech Enhancement via Discrete Audio Tokens](https://mlsanity.com/paper/2510.02187/) (2025)
- [Personalized Speech Enhancement Without a Separate Speaker Embedding Model](https://mlsanity.com/paper/2406.09928/) (2024)
- [Post-Training Speech Enhancement Language Models with Perceptual Rewards](https://mlsanity.com/paper/2606.21458/) (2026)

## 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).