# ICASSP 2021 Deep Noise Suppression Challenge: Decoupling Magnitude and Phase Optimization with a Two-Stage Deep Network

arXiv: https://arxiv.org/abs/2102.04198 · HTML: https://mlsanity.com/paper/2102.04198/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Feb 2021.

## Built on by (most cited first, 6 of 6)

- [TeleAntiFraud-28k: An Audio-Text Slow-Thinking Dataset for Telecom Fraud Detection](https://mlsanity.com/paper/2503.24115/) (2025)
- [A Mask Free Neural Network for Monaural Speech Enhancement](https://mlsanity.com/paper/2306.04286/) (2023)
- [A Two-stage Complex Network using Cycle-consistent Generative Adversarial Networks for Speech Enhancement](https://mlsanity.com/paper/2109.02011/) (2021)
- [Extending DNN-based Multiplicative Masking to Deep Subband Filtering for Improved Dereverberation](https://mlsanity.com/paper/2303.00529/) (2023)
- [A neural network-supported two-stage algorithm for lightweight dereverberation on hearing devices](https://mlsanity.com/paper/2204.02978/) (2022)
- [Contrastive Knowledge Distillation for Embedding Refinement in Personalized Speech Enhancement](https://mlsanity.com/paper/2601.16235/) (2026)

## Abstract (arXiv)

It remains a tough challenge to recover the speech signals contaminated by various noises under real acoustic environments. To this end, we propose a novel system for denoising in the complicated applications, which is mainly comprised of two pipelines, namely a two-stage network and a post-processing module. The first pipeline is proposed to decouple the optimization problem w:r:t: magnitude and phase, i.e., only the magnitude is estimated in the first stage and both of them are further refined in the second stage. The second pipeline aims to further suppress the remaining unnatural distorted noise, which is demonstrated to sufficiently improve the subjective quality. In the ICASSP 2021 Deep Noise Suppression (DNS) Challenge, our submitted system ranked top-1 for the real-time track 1 in terms of Mean Opinion Score (MOS) with ITU-T P.808 framework.