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01FluidInference /cv-corpus-25.0-ja Mozilla Common Voice 25.0 - Japanese Test Set (Complete) Dataset Description Complete Japanese test set from Mozilla Common Voice Corpus 25.0. This dataset contains all 9,019 validated test samples, compared to the partial 2,334-sample version previously available on HuggingFace. Key Features Size: 9,019 validated test utterances Coverage: 100% of official Common Voice 25.0 Japanese test split Multi-speaker: Diverse set of speakers with demographic metadata… See the full description on the dataset page: https://huggingface.co/datasets/FluidInference/cv-corpus-25.0-ja.audioautomatic-speech-recognition1K<n<10K0 likes160 downloads6mo agoHugging Face02fluffypotatoes /f1-team-radio F1 Team Radio Dataset A comprehensive dataset of Formula 1 team radio communications with transcriptions. Dataset Description This dataset contains team radio audio clips from Formula 1 races along with their text transcriptions. Team radio communications are the real-time messages exchanged between F1 drivers and their pit wall engineers during race weekends. Dataset Statistics Metric Value Total audio clips 14,681 Grand Prix events 149 Unique… See the full description on the dataset page: https://huggingface.co/datasets/fluffypotatoes/f1-team-radio.audioautomatic-speech-recognition10K<n<100K0 likes56 downloads5mo agoHugging Face03Batuka0901 /fluers-mn fleurs-mn Mongolian speech recognition dataset , recombined and split into a 90% train and 10% test set. Dataset Statistics Total samples: 4,428Total duration: 15h 33m 10s (15.55 h) Per-split breakdown Split Samples Total Duration Avg Duration train 3,985 13h 56m 57s (13.95 h) 12.60 s test 443 1h 36m 13s (1.60 h) 13.03 s audioautomatic-speech-recognition1K<n<10K1 likes10 downloads5mo agoHugging Face04johnbean393 /fluid-2-sft-asrgated Fluid 2 — synthetic dictation cleanup Fluid 2 is an English supervised-fine-tuning corpus for models that turn noisy automatic-speech-recognition output into the written insertion a user intended. It contains 354,549 rows in official document-grouped 96/2/2 splits, 861.3 hours of processed 16 kHz speech, and 8.48M target-side loss tokens in 355 Parquet shards (49.25 GiB). This is not an ordinary transcription dataset. The model sees document context plus an ASR hypothesis and… See the full description on the dataset page: https://huggingface.co/datasets/johnbean393/fluid-2-sft-asr.audiotext-generation100K<n<1M0 likes7 downloads1mo agoHugging Face

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