# Two Heads Are Better Than One: A Two-Stage Approach for Monaural Noise Reduction in the Complex Domain

arXiv: https://arxiv.org/abs/2011.01561 · HTML: https://mlsanity.com/paper/2011.01561/

## Key facts

- Cited by 3 papers in the map (data through 19 Oct 2026).
- First posted on arXiv 3 Nov 2020.

## Built on by (most cited first, 3 of 3)

- [Speech Enhancement Using Multi-Stage Self-Attentive Temporal Convolutional Networks](https://mlsanity.com/paper/2102.12078/) (2021)
- [Deep Interaction between Masking and Mapping Targets for Single-Channel Speech Enhancement](https://mlsanity.com/paper/2106.04878/) (2021)
- [Incorporating Multi-Target in Multi-Stage Speech Enhancement Model for Better Generalization](https://mlsanity.com/paper/2107.04232/) (2021)

## Abstract (arXiv)

In low signal-to-noise ratio conditions, it is difficult to effectively recover the magnitude and phase information simultaneously. To address this problem, this paper proposes a two-stage algorithm to decouple the joint optimization problem w.r.t. magnitude and phase into two sub-tasks. In the first stage, only magnitude is optimized, which incorporates noisy phase to obtain a coarse complex clean speech spectrum estimation. In the second stage, both the magnitude and phase components are refined. The experiments are conducted on the WSJ0-SI84 corpus, and the results show that the proposed approach significantly outperforms previous baselines in terms of PESQ, ESTOI, and SDR.