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AISHELL-1: An Open-Source Mandarin Speech Corpus and A Speech Recognition Baseline

arXiv 1709.05522 ↗First posted 16 Sep 2017cs.CLcited by 364

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Abstract (arXiv)

An open-source Mandarin speech corpus called AISHELL-1 is released. It is by far the largest corpus which is suitable for conducting the speech recognition research and building speech recognition systems for Mandarin. The recording procedure, including audio capturing devices and environments are presented in details. The preparation of the related resources, including transcriptions and lexicon are described. The corpus is released with a Kaldi recipe. Experimental results implies that the quality of audio recordings and transcriptions are promising.

Key facts. Cited by 364 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Sep 2017.

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Citing papers per year: 2021: 51; 2022: 53; 2023: 62; 2024: 69; 2025: 76; 2026: 53.

364 papers.

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  1. 2023A Survey on Multimodal Large Language Modelscited by 898
  2. 2023Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Modelscited by 591
  3. 2021SpeechBrain: A General-Purpose Speech Toolkitcited by 404
  4. 2022Self-Supervised Speech Representation Learning: A Reviewcited by 258
  5. 2025Kimi-Audio Technical Reportcited by 210
  6. 2025VITA-1.5: Towards GPT-4o Level Real-Time Vision and Speech Interactioncited by 191
  7. 2021WenetSpeech: A 10000+ Hours Multi-domain Mandarin Corpus for Speech Recognitioncited by 189
  8. 2021A Survey on Neural Speech Synthesiscited by 182
  9. 2022Paraformer: Fast and Accurate Parallel Transformer for Non-autoregressive End-to-End Speech Recognitioncited by 139
  10. 2024Freeze-Omni: A Smart and Low Latency Speech-to-speech Dialogue Model with Frozen LLMcited by 135
  11. 2021DistilHuBERT: Speech Representation Learning by Layer-wise Distillation of Hidden-unit BERTcited by 129
  12. 2023X-LLM: Bootstrapping Advanced Large Language Models by Treating Multi-Modalities as Foreign Languagescited by 127
38 more
  1. 2021WeNet: Production oriented Streaming and Non-streaming End-to-End Speech Recognition Toolkitcited by 123
  2. 2024FunAudioLLM: Voice Understanding and Generation Foundation Models for Natural Interaction Between Humans and LLMscited by 118
  3. 2024OmniBench: Towards The Future of Universal Omni-Language Modelscited by 100
  4. 2021Intermediate Loss Regularization for CTC-based Speech Recognitioncited by 95
  5. 2022ADD 2022: the First Audio Deep Synthesis Detection Challengecited by 94
  6. 2023FunASR: A Fundamental End-to-End Speech Recognition Toolkitcited by 92
  7. 2022Branchformer: Parallel MLP-Attention Architectures to Capture Local and Global Context for Speech Recognition and Understandingcited by 90
  8. 2025IndexTTS2: A Breakthrough in Emotionally Expressive and Duration-Controlled Auto-Regressive Zero-Shot Text-to-Speechcited by 85
  9. 2023LauraGPT: Listen, Attend, Understand, and Regenerate Audio with GPTcited by 77
  10. 2023Zipformer: A faster and better encoder for automatic speech recognitioncited by 77
  11. 2024OWSM v3.1: Better and Faster Open Whisper-Style Speech Models based on E-Branchformercited by 74
  12. 2024mHuBERT-147: A Compact Multilingual HuBERT Modelcited by 64
  13. 2026MiniCPM-o 4.5: Towards Real-Time Full-Duplex Omni-Modal Interactioncited by 64
  14. 2025Ming-Omni: A Unified Multimodal Model for Perception and Generationcited by 62
  15. 2021Relaxing the Conditional Independence Assumption of CTC-based ASR by Conditioning on Intermediate Predictionscited by 61
  16. 2025MiMo-Audio: Audio Language Models are Few-Shot Learnerscited by 58
  17. 2023LLaSM: Large Language and Speech Modelcited by 56
  18. 2024Towards Robust Speech Representation Learning for Thousands of Languagescited by 48
  19. 2024InternLM-XComposer2.5-OmniLive: A Comprehensive Multimodal System for Long-term Streaming Video and Audio Interactionscited by 48
  20. 2022WeNet 2.0: More Productive End-to-End Speech Recognition Toolkitcited by 46
  21. 2023FunCodec: A Fundamental, Reproducible and Integrable Open-source Toolkit for Neural Speech Codeccited by 44
  22. 2024EMOVA: Empowering Language Models to See, Hear and Speak with Vivid Emotionscited by 44
  23. 2021Interspeech 2021 Deep Noise Suppression Challengecited by 43
  24. 2021FastCorrect: Fast Error Correction with Edit Alignment for Automatic Speech Recognitioncited by 43
  25. 2021ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversationcited by 43
  26. 2023Reproducing Whisper-Style Training Using an Open-Source Toolkit and Publicly Available Datacited by 42
  27. 2023Exploring Speech Recognition, Translation, and Understanding with Discrete Speech Units: A Comparative Studycited by 42
  28. 2023HyPoradise: An Open Baseline for Generative Speech Recognition with Large Language Modelscited by 41
  29. 2021An Exploration of Self-Supervised Pretrained Representations for End-to-End Speech Recognitioncited by 39
  30. 2025Towards Holistic Evaluation of Large Audio-Language Models: A Comprehensive Surveycited by 38
  31. 2022Open Source MagicData-RAMC: A Rich Annotated Mandarin Conversational(RAMC) Speech Datasetcited by 36
  32. 2024OWSM-CTC: An Open Encoder-Only Speech Foundation Model for Speech Recognition, Translation, and Language Identificationcited by 34
  33. 2024GigaSpeech 2: An Evolving, Large-Scale and Multi-domain ASR Corpus for Low-Resource Languages with Automated Crawling, Transcription and Refinementcited by 34
  34. 2021Fast End-to-End Speech Recognition via Non-Autoregressive Models and Cross-Modal Knowledge Transferring from BERTcited by 31
  35. 2025VITA-Audio: Fast Interleaved Cross-Modal Token Generation for Efficient Large Speech-Language Modelcited by 30
  36. 2026LongCat-Next: Lexicalizing Modalities as Discrete Tokenscited by 30
  37. 2021U2++: Unified Two-pass Bidirectional End-to-end Model for Speech Recognitioncited by 28
  38. 2021FastCorrect 2: Fast Error Correction on Multiple Candidates for Automatic Speech Recognitioncited by 27

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