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Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.

modalityAllTextImageAudioTabularVideo
taskAllText generationQuestion answeringImage classificationSpeech
sizeAllUnder 1K1K – 10K100K – 1M1M – 10M
formatAllParquetJSONCSVWebDataset
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01malaiwah /qwen3-tts-customvoice-ab-clips qwen3-tts: full 5-way cloning comparison + cross-row diagnostic Generated 2026-04-14 on RTX 4080 SUPER. Directories original/ CustomVoice.generate_custom_voice(speaker=X) -> the ground truth voice clone/ Base.generate_voice_clone(ref_audio=original.wav, ref_text=...) -> full ICL clone via Base's own speaker encoder transplant/ Base.generate_voice_clone(voice_clone_prompt=[row]) x_vector_only_mode=True… See the full description on the dataset page: https://huggingface.co/datasets/malaiwah/qwen3-tts-customvoice-ab-clips.audion<1K0 likes212 downloads5mo agoHugging Face02erzhanbakanbayev /kk-yt-clipsaudio1K<n<10K0 likes168 downloads1y agoHugging Face03Jingya /video-clips-and-imgsaudion<1K0 likes96 downloads1mo agoHugging Face04Blasteur19 /data-clipaudion<1K0 likes72 downloads4mo agoHugging Face05GiusMagi /spyken-clipsaudio10K<n<100K0 likes56 downloads10d agoHugging Face06Gyimah3 /zulu-music-listening-clipsaudion<1K0 likes43 downloads1mo agoHugging Face07benmainbird /watermarking-clips Neural Watermarking Clips Summary This dataset contains 31 284 short audio clips collected as an unlabeled corpus for neural audio watermarking experiments. The clips cover environmental sounds, bird vocalizations, polyphonic music with predominant instruments and synthetic but realistic jazz drums and ragtime style piano. Source folders and file counts ARCA23K.audio 13 470 clips ff101bird 7 690 clips IRMAS training 6 706 clips WaivOps ragtime piano 1 743 clips WaivOps… See the full description on the dataset page: https://huggingface.co/datasets/benmainbird/watermarking-clips.audioaudio-classification10K<n<100K0 likes32 downloads10mo agoHugging Face08noflm /jdd_topic1_20251224-cliponly_sample100audio1K<n<10K0 likes30 downloads9mo agoHugging Face09HamdanXI /uclass_clipped_labeled Dataset Card for "uclass_clipped_labeled" More Information needed audio1K<n<10K0 likes29 downloads2y agoHugging Face10BonusLockSMith /1776-track-clips 1776 Track Clips Fast, wordless, loop-safe background music built for Shorts, Reels, and edits. This dataset contains 1776 unique audio clips designed for creators, editors, and developers who need clean, reusable background music without lyrics. What’s included 1776 unique clips No lyrics (wordless hooks) Clean, loop-safe structure Optimized for short-form video Editor-first design Preview See the preview video(s) in this repository for examples across… See the full description on the dataset page: https://huggingface.co/datasets/BonusLockSMith/1776-track-clips.audio1K<n<10K0 likes28 downloads9mo agoHugging Face11isabelarvelo /sep28k-train-4-second-clips Dataset Card for "sep28k-train-4-second-clips" More Information needed audio1K<n<10K0 likes26 downloads2y agoHugging Face12knoriy /OE-DCT-Movie-clipstabular10K<n<100K0 likes25 downloads3y agoHugging Face13Diffusion-ASR /worst100-testclean-clips Worst-100 test-clean clips — audio, transcripts, and the vocabulary finding The 100 LibriSpeech test-clean clips where the block-4 production model (4.60% WER) made the most word errors — with audio embedded so the failures can be listened to, plus the model's transcript next to the reference for each clip. The finding this dataset produced 47% of the word errors in these clips are on words that never appeared in the 30-hour training vocabulary at all (20,066… See the full description on the dataset page: https://huggingface.co/datasets/Diffusion-ASR/worst100-testclean-clips.audion<1K0 likes21 downloads2mo agoHugging Face14yongjian /music-clips-50There are 50 music clips(of 3~5 seconds). You can load them by the following code: from datasets import load_dataset dataset = load_dataset('yongjian/music-clips-50') clips = dataset['train'] # all 50 music clips music_1_np_array = clips[0]['audio']['array'] # numpy array of shape=[N,] Or you can directly download them from Google Drive: music-clips-50.tar.gz. audion<1K3 likes20 downloads4y agoHugging Face15isabelarvelo /sep28k-train-3-second-clips-full-agreement Dataset Card for "sep28k-train-3-second-clips-full-agreement" More Information needed audio1K<n<10K0 likes18 downloads2y agoHugging Face16isabelarvelo /sep28k-train-5-second-clips Dataset Card for "sep28k-train-5-second-clips" More Information needed audio1K<n<10K0 likes17 downloads2y agoHugging Face17isabelarvelo /sep28k-dev-5-second-clips Dataset Card for "sep28k-dev-5-second-clips" More Information needed audio1K<n<10K0 likes17 downloads2y agoHugging Face18isabelarvelo /sep28k-test-4-second-clips Dataset Card for "sep28k-test-0120-4-second-clips" More Information needed audio1K<n<10K0 likes16 downloads2y agoHugging Face19isabelarvelo /sep28k-test-5-second-clips Dataset Card for "sep28k-test-5-second-clips" More Information needed audio1K<n<10K0 likes16 downloads2y agoHugging Face20isabelarvelo /sep28k-dev-4-second-clips Dataset Card for "sep28k-dev-0120-4-second-clips" More Information needed audio1K<n<10K0 likes15 downloads2y agoHugging Face21isabelarvelo /fluencybank-3-second-clips Dataset Card for "fluencybank-3-second-clips" More Information needed audio1K<n<10K0 likes15 downloads2y agoHugging Face22isabelarvelo /sep28k-train-3-second-clips Dataset Card for "sep28k-train-3-second-clips" More Information needed audio1K<n<10K0 likes15 downloads2y agoHugging Face23Clip11 /clip13audion<1K0 likes14 downloads3y agoHugging Face24isabelarvelo /sep28k-dev-3-second-clip-full-agreement Dataset Card for "sep28k-dev-3-second-clip-full-agreement" More Information needed audio1K<n<10K0 likes13 downloads2y agoHugging Face25sw-voice /swamiji-tail-artifact-clips Reported end-of-clip artifact: the raw clips The exact phrases reported as having "a weird sound at the end", straight out of the production engine, three independent draws each. No processing at all — this is what the model produced. phrase text doingwell I am doing well, thank you. hereif also I am here if you need anything. hereforyou I am here for you. welcome You are very welcome! glad Glad you think so! scope I can only answer about Sri Ganapati… See the full description on the dataset page: https://huggingface.co/datasets/sw-voice/swamiji-tail-artifact-clips.audiotext-to-speechn<1K0 likes13 downloads2mo agoHugging Face26isabelarvelo /fluencybank-4-second-clips Dataset Card for "fluencybank-4-second-clips" More Information needed audio1K<n<10K0 likes11 downloads2y agoHugging Face27sw-voice /swamiji-voice-clips-clean-transcribedaudion<1K0 likes11 downloads3mo agoHugging Face28isabelarvelo /sep28k-test-3-second-clips-full-agreement Dataset Card for "sep28k-test-3-second-clips-full-agreement" More Information needed audio1K<n<10K0 likes10 downloads2y agoHugging Face29isabelarvelo /sep28k-dev-3-second-clips Dataset Card for "sep28k-dev-3-second-clips" More Information needed audio1K<n<10K0 likes9 downloads2y agoHugging Face30ShaySha /trance_clipsaudion<1K0 likes8 downloads2y agoHugging Face

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