mlsanityData to 14 Oct 2026

LSTMSE-Net: Long Short Term Speech Enhancement Network for Audio-visual Speech Enhancement

arXiv 2409.02266 ↗First posted 3 Sep 2024cs.SD cs.LG cs.MMcited by 3

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Abstract (arXiv)

In this paper, we propose long short term memory speech enhancement network (LSTMSE-Net), an audio-visual speech enhancement (AVSE) method. This innovative method leverages the complementary nature of visual and audio information to boost the quality of speech signals. Visual features are extracted with VisualFeatNet (VFN), and audio features are processed through an encoder and decoder. The system scales and concatenates visual and audio features, then processes them through a separator network for optimized speech enhancement. The architecture highlights advancements in leveraging multi-modal data and interpolation techniques for robust AVSE challenge systems. The performance of LSTMSE-Net surpasses that of the baseline model from the COG-MHEAR AVSE Challenge 2024 by a margin of 0.06 in scale-invariant signal-to-distortion ratio (SISDR), 0.03 in short-time objective intelligibility (STOI), and 1.32 in perceptual evaluation of speech quality (PESQ). The source code of the proposed LSTMSE-Net is available at urlhttps://github.com/mtanveer1/AVSEC-3-Challenge.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 11 of its 27 references that are in the map. First posted on arXiv 3 Sep 2024.

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11 of 27 references.

References · 11

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2018LRS3-TED: a large-scale dataset for visual speech recognitioncited by 308
  3. 2020DCCRN: Deep Complex Convolution Recurrent Network for Phase-Aware Speech Enhancementcited by 141
  4. 2020The INTERSPEECH 2020 Deep Noise Suppression Challenge: Datasets, Subjective Testing Framework, and Challenge Resultscited by 133
  5. 2018The Conversation: Deep Audio-Visual Speech Enhancementcited by 109
  6. 2020An Overview of Deep-Learning-Based Audio-Visual Speech Enhancement and Separationcited by 81
  7. 2019Phase-aware Speech Enhancement with Deep Complex U-Netcited by 73
  8. 2020Discriminative Multi-modality Speech Recognitioncited by 58
  9. 2020Improved Lite Audio-Visual Speech Enhancementcited by 12
  10. 2022Audio-Visual Speech Enhancement and Separation by Utilizing Multi-Modal Self-Supervised Embeddingscited by 7
  11. 2023Leveraging Self-Supervised Audio-Visual Pretrained Models to Improve Vocoded Speech Intelligibility in Cochlear Implant Simulationcited by 4

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Cited by year

Citing papers per year: 2025: 3.

3 papers.

  1. 2025Bridging The Multi-Modality Gaps of Audio, Visual and Linguistic for Speech Enhancementcited by 3
  2. 2025AUREXA-SE: Audio-Visual Unified Representation Exchange Architecture with Cross-Attention and Squeezeformer for Speech Enhancementcited by 1
  3. 2025Lightweight Wasserstein Audio-Visual Model for Unified Speech Enhancement and Separationcited by 0