mlsanityData to 7 Oct 2026

Single-Channel Distance-Based Source Separation for Mobile GPU in Outdoor and Indoor Environments

arXiv 2501.03045 ↗First posted 6 Jan 2025eess.AS cs.AIcited by 0

Not on the map. Why?

Abstract (arXiv)

This study emphasizes the significance of exploring distance-based source separation (DSS) in outdoor environments. Unlike existing studies that primarily focus on indoor settings, the proposed model is designed to capture the unique characteristics of outdoor audio sources. It incorporates advanced techniques, including a two-stage conformer block, a linear relation-aware self-attention (RSA), and a TensorFlow Lite GPU delegate. While the linear RSA may not capture physical cues as explicitly as the quadratic RSA, the linear RSA enhances the model's context awareness, leading to improved performance on the DSS that requires an understanding of physical cues in outdoor and indoor environments. The experimental results demonstrated that the proposed model overcomes the limitations of existing approaches and considerably enhances energy efficiency and real-time inference speed on mobile devices.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 20 of its 34 references that are in the map. First posted on arXiv 6 Jan 2025.

Builds on

20 of 34 references.

References · 20

  1. 2017Attention Is All You Needcited by 59,932
  2. 2021RoFormer: Enhanced Transformer with Rotary Position Embeddingcited by 4,581
  3. 2020Conformer: Convolution-augmented Transformer for Speech Recognitioncited by 1,838
  4. 2019Generating Long Sequences with Sparse Transformerscited by 1,523
  5. 2018Self-Attention with Relative Position Representationscited by 1,112
  6. 2018SDR - half-baked or well done?cited by 420
  7. 2018Efficient Attention: Attention with Linear Complexitiescited by 366
  8. 2019Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separationcited by 182
  9. 2017Pyroomacoustics: A Python package for audio room simulations and array processing algorithmscited by 131
  10. 2020AISHELL-3: A Multi-speaker Mandarin TTS Corpus and the Baselinescited by 111
  11. 2019MetricGAN: Generative Adversarial Networks based Black-box Metric Scores Optimization for Speech Enhancementcited by 104
  12. 2022CMGAN: Conformer-based Metric GAN for Speech Enhancementcited by 45
8 more
  1. 2018Compact Generalized Non-local Networkcited by 36
  2. 2020Continuous Speech Separation with Conformercited by 36
  3. 2019LatentGNN: Learning Efficient Non-local Relations for Visual Recognitioncited by 25
  4. 2020A consolidated view of loss functions for supervised deep learning-based speech enhancementcited by 19
  5. 2022Distance-Based Sound Separationcited by 7
  6. 2021On permutation invariant training for speech source separationcited by 4
  7. 2024Hyperbolic Distance-Based Speech Separationcited by 4
  8. 2023Focus on the Sound around You: Monaural Target Speaker Extraction via Distance and Speaker Informationcited by 3

Built on by

Not cited yet.