mlsanityData to 19 Oct 2026

The PCG-AIID System for L3DAS22 Challenge: MIMO and MISO convolutional recurrent Network for Multi Channel Speech Enhancement and Speech Recognition

arXiv 2202.10017 ↗First posted 21 Feb 2022eess.AS cs.SDcited by 4

On the map: Speech and audio language models → Speech enhancement and noise suppression

Abstract (arXiv)

This paper described the PCG-AIID system for L3DAS22 challenge in Task 1: 3D speech enhancement in office reverberant environment. We proposed a two-stage framework to address multi-channel speech denoising and dereverberation. In the first stage, a multiple input and multiple output (MIMO) network is applied to remove background noise while maintaining the spatial characteristics of multi-channel signals. In the second stage, a multiple input and single output (MISO) network is applied to enhance the speech from desired direction and post-filtering. As a result, our system ranked 3rd place in ICASSP2022 L3DAS22 challenge and significantly outperforms the baseline system, while achieving 3.2% WER and 0.972 STOI on the blind test-set.

Key facts. Cited by 4 papers in the map (data through 19 Oct 2026). Placed in Speech enhancement and noise suppression, one of 11 directions in Speech and audio language models. Builds on 6 of its 18 references that are in the map. First posted on arXiv 21 Feb 2022.

Builds on

6 of 18 references.

References · 6

  1. 2020wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representationscited by 4,385
  2. 2020FSD50K: An Open Dataset of Human-Labeled Sound Eventscited by 395
  3. 2017Supervised Speech Separation Based on Deep Learning: An Overviewcited by 342
  4. 2020ADL-MVDR: All deep learning MVDR beamformer for target speech separationcited by 40
  5. 2020Multi-Microphone Complex Spectral Mapping for Speech Dereverberationcited by 25
  6. 2021Inplace Gated Convolutional Recurrent Neural Network For Dual-channel Speech Enhancementcited by 5

Built on by

Cited by year

Citing papers per year: 2022: 2; 2023: 1; 2024: 0; 2025: 1.

4 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2022Towards Low-distortion Multi-channel Speech Enhancement: The ESPNet-SE Submission to The L3DAS22 Challenge
  2. 2022Insights Into Deep Non-linear Filters for Improved Multi-channel Speech Enhancement
  3. 2021Multichannel Speech Enhancement without Beamforming
  4. 2022On the Role of Spatial, Spectral, and Temporal Processing for DNN-based Non-linear Multi-channel Speech Enhancement
  5. 2022spatial-dccrn: dccrn equipped with frame-level angle feature and hybrid filtering for multi-channel speech enhancement
  6. 2021Towards efficient models for real-time deep noise suppression
  7. 2022Speech Enhancement with Intelligent Neural Homomorphic Synthesis
  8. 2025A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR Conditions