# A two-stage speaker extraction algorithm under adverse acoustic conditions using a single-microphone

arXiv: https://arxiv.org/abs/2303.07072 · HTML: https://mlsanity.com/paper/2303.07072/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Mar 2023.

## Built on by (most cited first, 2 of 2)

- [Socially Pertinent Robots in Gerontological Healthcare](https://mlsanity.com/paper/2404.07560/) (2024)
- [End-to-End Multi-Microphone Speaker Extraction Using Relative Transfer Functions](https://mlsanity.com/paper/2502.06285/) (2025)

## Abstract (arXiv)

In this work, we present a two-stage method for speaker extraction under reverberant and noisy conditions. Given a reference signal of the desired speaker, the clean, but the still reverberant, desired speaker is first extracted from the noisy-mixed signal. In the second stage, the extracted signal is further enhanced by joint dereverberation and residual noise and interference reduction. The proposed architecture comprises two sub-networks, one for the extraction task and the second for the dereverberation task. We present a training strategy for this architecture and show that the performance of the proposed method is on par with other state-of-the-art (SOTA) methods when applied to the WHAMR! dataset. Furthermore, we present a new dataset with more realistic adverse acoustic conditions and show that our method outperforms the competing methods when applied to this dataset as well.