mlsanityData to 7 Oct 2026

The Accented English Speech Recognition Challenge 2020: Open Datasets, Tracks, Baselines, Results and Methods

arXiv 2102.10233 ↗First posted 20 Feb 2021cs.SD eess.AScited by 24

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Abstract (arXiv)

The variety of accents has posed a big challenge to speech recognition. The Accented English Speech Recognition Challenge (AESRC2020) is designed for providing a common testbed and promoting accent-related research. Two tracks are set in the challenge -- English accent recognition (track 1) and accented English speech recognition (track 2). A set of 160 hours of accented English speech collected from 8 countries is released with labels as the training set. Another 20 hours of speech without labels is later released as the test set, including two unseen accents from another two countries used to test the model generalization ability in track 2. We also provide baseline systems for the participants. This paper first reviews the released dataset, track setups, baselines and then summarizes the challenge results and major techniques used in the submissions.

Key facts. Cited by 24 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Feb 2021.

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Citing papers per year: 2021: 3; 2022: 4; 2023: 4; 2024: 4; 2025: 4; 2026: 5.

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  1. 2023The Edinburgh International Accents of English Corpus: Towards the Democratization of English ASRcited by 36
  2. 2026OmniVoice: Towards Omnilingual Zero-Shot Text-to-Speech with Diffusion Language Modelscited by 22
  3. 2024Speech Robust Bench: A Robustness Benchmark For Speech Recognitioncited by 20
  4. 2023CommonAccent: Exploring Large Acoustic Pretrained Models for Accent Classification Based on Common Voicecited by 19
  5. 2023What Can an Accent Identifier Learn? Probing Phonetic and Prosodic Information in a Wav2vec2-based Accent Identification Modelcited by 18
  6. 2021Speech Technology for Everyone: Automatic Speech Recognition for Non-Native English with Transfer Learningcited by 9
  7. 2024AccentBox: Towards High-Fidelity Zero-Shot Accent Generationcited by 9
  8. 2021Towards the evaluation of automatic simultaneous speech translation from a communicative perspectivecited by 8
  9. 2021Wav2vec-S: Semi-Supervised Pre-Training for Low-Resource ASRcited by 7
  10. 2026PRiSM: Benchmarking Phone Realization in Speech Modelscited by 4
  11. 2022Improving Automatic Speech Recognition for Non-Native English with Transfer Learning and Language Model Decodingcited by 3
  12. 2022A One-shot Framework for Distributed Clustered Learning in Heterogeneous Environmentscited by 3
12 more
  1. 2023Decoupled Structure for Improved Adaptability of End-to-End Modelscited by 3
  2. 2022Using Chatbots to Teach Languagescited by 2
  3. 2025Accent-Invariant Automatic Speech Recognition via Saliency-Driven Spectrogram Maskingcited by 2
  4. 2022Low-resource Accent Classification in Geographically-proximate Settings: A Forensic and Sociophonetics Perspectivecited by 1
  5. 2025LID Models are Actually Accent Classifiers: Implications and Solutions for LID on Accented Speechcited by 1
  6. 2024GE2E-AC: Generalized End-to-End Loss Training for Accent Classificationcited by 0
  7. 2024Adapter-based Approaches to Knowledge-enhanced Language Models -- A Surveycited by 0
  8. 2025Proficiency-Aware Adaptation and Data Augmentation for Robust L2 ASRcited by 0
  9. 2025CLARITY: Contextual Linguistic Adaptation and Accent Retrieval for Dual-Bias Mitigation in Text-to-Speech Generationcited by 0
  10. 2026ACES: Accent Subspaces for Coupling, Explanations, and Stress-Testing in Automatic Speech Recognitioncited by 0
  11. 2026Proactive for Uncertainty: Cause-Aware Error Diagnosis and Interactive Clarification for Spoken Dialogue Systemscited by 0
  12. 2026Benchmarking_Fast_Domain_Adaptation_for_Unsupervised_Speech_Unitscited by 0