datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
multichannel-meetings-10h
GroundTruth Multi-Channel Meeting Audio Dataset (10h)
Summary
This dataset contains approximately 10 hours of co-located, multi-speaker meeting recordings, each captured simultaneously via a room (built-in) microphone and individual close-talk lapel microphones worn by each participant.
Each meeting includes:
One full meeting recording (room microphone)
Individual close-talk recordings for each participant (one file per speaker)
Structured metadata describing speakers… See the full description on the dataset page: https://huggingface.co/datasets/ground-truth/multichannel-meetings-10h.voice-code-bench
VoiceCodeBench
VoiceCodeBench is a test-only benchmark for evaluating whether automatic
speech recognition (ASR) systems preserve exact structured values in English
workplace speech.
Paper: VoiceCodeBench: Evaluating Exact Structured-Token Recovery in Automatic Speech Recognition
The benchmark targets cases where a transcript is software input: callback
numbers, email addresses, command-line flags, file paths, URLs, account
identifiers, dates, measurements, and similar values… See the full description on the dataset page: https://huggingface.co/datasets/yunqi1766/voice-code-bench.open-vi-dialog-synthetic-100h
OpenDialog Vietnamese Synthetic Dialogue 100h
Synthetic Vietnamese two-speaker dialogue for ZipVoice-Dialog experiments.
12,000 chunks
30 seconds per chunk
100.0 hours total
Each item contains S1/S2 speaker labels, turn timings, target text,
relationship, pronouns, environment, topic, mood, and source reference IDs.
Audio renderer: vLLM-Omni VoxCPM2
Audio format: mono WAV, 48 kHz, 30 seconds per chunk
This is a research dataset. Review the source/reference licensing and the… See the full description on the dataset page: https://huggingface.co/datasets/tsdocode/open-vi-dialog-synthetic-100h.uzbek-asr-train-manifests
Uzbek ASR Training Manifests
The exact training, validation and test splits behind
rustam1221/uzbek-asr-gigaam:
974 hours of Uzbek speech drawn from seven public corpora, filtered, text-normalized,
and split by speaker.
No audio is copied. Each row is a pointer — a parquet file plus a row
index in the upstream dataset — and the training dataloader decodes the audio
when the batch is built. That keeps the whole corpus definition at 200 MB
instead of roughly a terabyte of… See the full description on the dataset page: https://huggingface.co/datasets/rustam1221/uzbek-asr-train-manifests.arabic-english-code-switching-review-annotations
Review Annotations for Arabic-English Code-Switching Speech
This metadata-only dataset publishes review decisions and transcript-correction deltas for MohamedRashad/arabic-english-code-switching. It contains no human audio, no local file paths, no raw review notes, and no copies of unchanged upstream transcripts.
The annotations are pinned to upstream revision 4a3bffc45219c35949470de32b8d4cb328b0ce11 and join by upstream_row_index.
Coverage and outcomes
The… See the full description on the dataset page: https://huggingface.co/datasets/abdo1819/arabic-english-code-switching-review-annotations.advanced-soundscapes-stage-1
Advanced Soundscapes Stage 1 — Raw Components
This dataset contains Stage 1 output from the LAION Universal Audio Annotation Pipeline (UAAP) data generation plan.
Contents
0 shard(s) containing 0 soundscape recipes with raw audio components
Each soundscape row includes:
recipe.json — full recipe with timeline, events, loudness, speaker IDs, overlap/density settings
spkN.flac / spkN.json — raw speech components + full source metadata
musicN.flac / musicN.json —… See the full description on the dataset page: https://huggingface.co/datasets/ChristophSchuhmann/advanced-soundscapes-stage-1.audio-alpacaquantized-common-voice-enhindi-english-codeswitch-dataset
Hindi-English Code-Switch ASR Transcripts
Text transcripts and metadata for a large bilingual Hindi-English code-switch ASR training corpus, used to train Abhisingh-18/hindi-english-codeswitch-asr.
This release contains transcripts and metadata only — no audio files. Audio was sourced from multiple corpora and institutions and is not redistributed here.
Credits
Speech data collection and curation credit: SPRING Lab, IIT Madras.
Contents
File… See the full description on the dataset page: https://huggingface.co/datasets/Abhisingh-18/hindi-english-codeswitch-dataset.common-voice-en-revoiceyogera_runyankore_ailab_4_0_1eval
Dataset Card for Dataset Name
This dataset card aims to be a base template for new datasets. It has been generated using this raw template.
Dataset Details
Dataset Description
Curated by: jonathan harrison
Funded by [optional]: [More Information Needed]
Shared by [optional]: [More Information Needed]
Language(s) (NLP): [More Information Needed]
License: [More Information Needed]
Dataset Sources [optional]
Repository: [More Information… See the full description on the dataset page: https://huggingface.co/datasets/Raiff1982/eval.SPS-Bopha-Voice-Dataset-v1
VibeVoice Fine-Tuning Dataset: SPS-Bopha-Voice-Dataset-v1
This dataset is formatted for fine-tuning VibeVoice.
Structure
training_data.jsonl: The main manifest file containing transcriptions and paths.
chunks_staging/: Directory containing the audio clips.
Usage with VibeVoice
Clone this repository:
git clone https://huggingface.co/datasets/Tnaot/SPS-Bopha-Voice-Dataset-v1
cd SPS-Bopha-Voice-Dataset-v1
Run the training script pointing to… See the full description on the dataset page: https://huggingface.co/datasets/Tnaot/SPS-Bopha-Voice-Dataset-v1.nb-asr-qwen3whisperxagreement-v1
nb-asr-qwen3whisperxagreement-v1
Word-level forced alignment training data for Norwegian speech, produced by keeping only examples where two independent aligners — WhisperX and Qwen3 (Lunde forced aligner) — agree within a tight tolerance.
Dataset Description
This dataset contains 702,067 speech segments drawn from the NB-ASR Norwegian audio corpus. Each record pairs an audio file with a word-level forced alignment in a format suitable for training a… See the full description on the dataset page: https://huggingface.co/datasets/NbAiLab/nb-asr-qwen3whisperxagreement-v1.quantized-librispeech-train-360medimind-r11-train
MediMind R11 — ASR training data
Unified manifest + packed audio for fine-tuning Whisper-large-v3 on Norwegian
clinical and conversational speech.
Training manifest: r11_manifest.jsonl — 11,022 packs
Held-out eval set: r11_heldout_eval.jsonl — 291 packs (NEVER train on these)
~see manifest audit packs total
11 sources: lege_*, podcasts (motiv/podk/stet), nb_samtale, nb_tale_m3, tts_drugs
Schema
See r11_manifest.jsonl (one JSON object per line) and… See the full description on the dataset page: https://huggingface.co/datasets/gallip0li/medimind-r11-train.