mlsanityData to 7 Oct 2026

Far-Field Automatic Speech Recognition

arXiv 2009.09395 ↗First posted 20 Sep 2020eess.AScited by 32

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Abstract (arXiv)

The machine recognition of speech spoken at a distance from the microphones, known as far-field automatic speech recognition (ASR), has received a significant increase of attention in science and industry, which caused or was caused by an equally significant improvement in recognition accuracy. Meanwhile it has entered the consumer market with digital home assistants with a spoken language interface being its most prominent application. Speech recorded at a distance is affected by various acoustic distortions and, consequently, quite different processing pipelines have emerged compared to ASR for close-talk speech. A signal enhancement front-end for dereverberation, source separation and acoustic beamforming is employed to clean up the speech, and the back-end ASR engine is robustified by multi-condition training and adaptation. We will also describe the so-called end-to-end approach to ASR, which is a new promising architecture that has recently been extended to the far-field scenario. This tutorial article gives an account of the algorithms used to enable accurate speech recognition from a distance, and it will be seen that, although deep learning has a significant share in the technological breakthroughs, a clever combination with traditional signal processing can lead to surprisingly effective solutions.

Key facts. Cited by 32 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Sep 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 5; 2022: 10; 2023: 9; 2024: 2; 2025: 3; 2026: 3.

32 papers.

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  1. 2022Conditional Diffusion Probabilistic Model for Speech Enhancementcited by 132
  2. 2022u-HuBERT: Unified Mixed-Modal Speech Pretraining And Zero-Shot Transfer to Unlabeled Modalitycited by 36
  3. 2021Multi-Channel Transformer Transducer for Speech Recognitioncited by 8
  4. 2023Perceive and predict: self-supervised speech representation based loss functions for speech enhancementcited by 8
  5. 2025Hearing Anywhere in Any Environmentcited by 8
  6. 2022A Conformer Based Acoustic Model for Robust Automatic Speech Recognitioncited by 6
  7. 2022Receptive Field Analysis of Temporal Convolutional Networks for Monaural Speech Dereverberationcited by 6
  8. 2022MetricGAN+/-: Increasing Robustness of Noise Reduction on Unseen Datacited by 5
  9. 2025BERSting at the Screams: A Benchmark for Distanced, Emotional and Shouted Speech Recognitioncited by 5
  10. 2021Self-Attention Channel Combinator Frontend for End-to-End Multichannel Far-field Speech Recognitioncited by 4
  11. 2023UNSSOR: Unsupervised Neural Speech Separation by Leveraging Over-determined Training Mixturescited by 4
  12. 2023Audio-visual End-to-end Multi-channel Speech Separation, Dereverberation and Recognitioncited by 4
20 more
  1. 2021Dual-Encoder Architecture with Encoder Selection for Joint Close-Talk and Far-Talk Speech Recognitioncited by 3
  2. 2022Utterance Weighted Multi-Dilation Temporal Convolutional Networks for Monaural Speech Dereverberationcited by 3
  3. 2022Deformable Temporal Convolutional Networks for Monaural Noisy Reverberant Speech Separationcited by 3
  4. 2023The Effect of Spoken Language on Speech Enhancement using Self-Supervised Speech Representation Loss Functionscited by 3
  5. 2023Speech enhancement with frequency domain auto-regressive modelingcited by 3
  6. 2023On Time Domain Conformer Models for Monaural Speech Separation in Noisy Reverberant Acoustic Environmentscited by 3
  7. 2022Reverberation as Supervision for Speech Separationcited by 2
  8. 2023On Data Sampling Strategies for Training Neural Network Speech Separation Modelscited by 2
  9. 2023Convoifilter: A case study of doing cocktail party speech recognitioncited by 2
  10. 2022End-to-End Multi-speaker ASR with Independent Vector Analysiscited by 1
  11. 2024Transcription-Free Fine-Tuning of Speech Separation Models for Noisy and Reverberant Multi-Speaker Automatic Speech Recognitioncited by 1
  12. 2024Out-of-distribution generalisation in spoken language understandingcited by 1
  13. 2025A Synergistic Framework of Nonlinear Acoustic Computing and Reinforcement Learning for Real-World Human-Robot Interactioncited by 1
  14. 2026ASKD-Whisper: Adaptive Self-knowledge Distillation for Efficient and Low-Latency Automatic Speech Recognitioncited by 1
  15. 2021Scaling sparsemax based channel selection for speech recognition with ad-hoc microphone arrayscited by 0
  16. 2021Do You Listen with One or Two Microphones? A Unified ASR Model for Single and Multi-Channel Audiocited by 0
  17. 2022Spatial Processing Front-End For Distant ASR Exploiting Self-Attention Channel Combinatorcited by 0
  18. 2023RIR-SF: Room Impulse Response Based Spatial Feature for Target Speech Recognition in Multi-Channel Multi-Speaker Scenarioscited by 0
  19. 2026Joint Enhancement and Classification using Coupled Diffusion Models of Signals and Logitscited by 0
  20. 2026Who Spoke What When? Evaluating Spoken Language Models for Conversational ASR with Semantic and Overlap-Aware Metricscited by 0