mlsanityData to 7 Oct 2026

FSD50K: An Open Dataset of Human-Labeled Sound Events

arXiv 2010.00475 ↗First posted 1 Oct 2020cs.SD cs.LG eess.AScited by 339

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Cited by 24 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Most existing datasets for sound event recognition (SER) are relatively small and/or domain-specific, with the exception of AudioSet, based on over 2M tracks from YouTube videos and encompassing over 500 sound classes. However, AudioSet is not an open dataset as its official release consists of pre-computed audio features. Downloading the original audio tracks can be problematic due to YouTube videos gradually disappearing and usage rights issues. To provide an alternative benchmark dataset and thus foster SER research, we introduce FSD50K, an open dataset containing over 51k audio clips totalling over 100h of audio manually labeled using 200 classes drawn from the AudioSet Ontology. The audio clips are licensed under Creative Commons licenses, making the dataset freely distributable (including waveforms). We provide a detailed description of the FSD50K creation process, tailored to the particularities of Freesound data, including challenges encountered and solutions adopted. We include a comprehensive dataset characterization along with discussion of limitations and key factors to allow its audio-informed usage. Finally, we conduct sound event classification experiments to provide baseline systems as well as insight on the main factors to consider when splitting Freesound audio data for SER. Our goal is to develop a dataset to be widely adopted by the community as a new open benchmark for SER research.

Key facts. Cited by 339 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Oct 2020.

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Citing papers per year: 2021: 25; 2022: 33; 2023: 45; 2024: 59; 2025: 97; 2026: 80.

339 papers.

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  1. 2022High Fidelity Neural Audio Compressioncited by 673
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  4. 2021Efficient Training of Audio Transformers with Patchoutcited by 222
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  10. 2024WavTokenizer: an Efficient Acoustic Discrete Codec Tokenizer for Audio Language Modelingcited by 124
  11. 2023ONE-PEACE: Exploring One General Representation Model Toward Unlimited Modalitiescited by 117
  12. 2021BYOL for Audio: Self-Supervised Learning for General-Purpose Audio Representationcited by 106
38 more
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  6. 2024A Survey of Multimodal Large Language Model from A Data-centric Perspectivecited by 73
  7. 2024Codec Does Matter: Exploring the Semantic Shortcoming of Codec for Audio Language Modelcited by 70
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  9. 2025OmniVinci: Enhancing Architecture and Data for Omni-Modal Understanding LLMcited by 53
  10. 2024InternLM-XComposer2.5-OmniLive: A Comprehensive Multimodal System for Long-term Streaming Video and Audio Interactionscited by 48
  11. 2023Epic-Sounds: A Large-scale Dataset of Actions That Soundcited by 47
  12. 2025DeSTA2.5-Audio: Toward General-Purpose Large Audio Language Model with Self-Generated Cross-Modal Alignmentcited by 47
  13. 2023Separate Anything You Describecited by 43
  14. 2023CompA: Addressing the Gap in Compositional Reasoning in Audio-Language Modelscited by 43
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  17. 2025M-Prometheus: A Suite of Open Multilingual LLM Judgescited by 37
  18. 2024BirdSet: A Large-Scale Dataset for Audio Classification in Avian Bioacousticscited by 36
  19. 2023Cross-Modal Fine-Tuning: Align then Refinecited by 34
  20. 2021NAS-Bench-360: Benchmarking Neural Architecture Search on Diverse Taskscited by 32
  21. 2024DASB - Discrete Audio and Speech Benchmarkcited by 32
  22. 2025Investigation of Whisper ASR Hallucinations Induced by Non-Speech Audiocited by 31
  23. 2022XKD: Cross-modal Knowledge Distillation with Domain Alignment for Video Representation Learningcited by 30
  24. 2023Self-supervised Audio Teacher-Student Transformer for Both Clip-level and Frame-level Taskscited by 25
  25. 2024Both Ears Wide Open: Towards Language-Driven Spatial Audio Generationcited by 25
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  27. 2022MetaAudio: A Few-Shot Audio Classification Benchmarkcited by 24
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  29. 2024Towards Open Respiratory Acoustic Foundation Models: Pretraining and Benchmarkingcited by 23
  30. 2025AnyEnhance: A Unified Generative Model with Prompt-Guidance and Self-Critic for Voice Enhancementcited by 23
  31. 2023From Discrete Tokens to High-Fidelity Audio Using Multi-Band Diffusioncited by 22
  32. 2025FreeAudio: Training-Free Timing Planning for Controllable Long-Form Text-to-Audio Generationcited by 21
  33. 2022RemixIT: Continual self-training of speech enhancement models via bootstrapped remixingcited by 20
  34. 2023The CHiME-7 DASR Challenge: Distant Meeting Transcription with Multiple Devices in Diverse Scenarioscited by 20
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  36. 2022Efficient Architecture Search for Diverse Taskscited by 18
  37. 2024Prompt-guided Precise Audio Editing with Diffusion Modelscited by 18
  38. 2025The iNaturalist Sounds Datasetcited by 17

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