datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
seamless-interaction
Seamless Interaction Dataset
A large-scale multimodal dataset of 4,000+ hours of human interactions for AI research
🖼️ Blog
🌐 Website
🎮 Demo
📦 GitHub
📄 Paper
Human communication involves a complex interplay of verbal and nonverbal signals, essential for conveying meaning and achieving interpersonal goals.
The Seamless Interaction Dataset is a large-scale collection of over 4,000 hours of face-to-face interaction footage from more than 4,000 participants in… See the full description on the dataset page: https://huggingface.co/datasets/facebook/seamless-interaction.audiofolder_single_config_in_metadatamultilingual-speech-commands-15lang
Multilingual Speech Commands Dataset (15 Languages, Augmented)
This dataset contains augmented speech command samples in 15 languages, derived from multiple public datasets. Only commands that overlap with the Google Speech Commands (GSC) vocabulary are included, making the dataset suitable for multilingual keyword spotting tasks aligned with GSC-style classification.
Audio samples have been augmented using standard audio techniques to improve model robustness (e.g., time-shifting… See the full description on the dataset page: https://huggingface.co/datasets/artur-muratov/multilingual-speech-commands-15lang.whisper_transcriptions.reazon_speech_allvoxbox
VoxBox
This dataset is a curated collection of bilingual speech corpora annotated clean transcriptions and rich metadata incluing age, gender, and emotion.
Dataset Structure
.
├── audios/
│ └── aishell-3/ # Audio files (organised by sub-corpus)
│ └── ...
└── metadata/
├── aishell-3.jsonl
├── casia.jsonl
├── commonvoice_cn.jsonl
├── ...
└── wenetspeech4tts.jsonl # JSONL metadata files
Each JSONL file corresponds to a… See the full description on the dataset page: https://huggingface.co/datasets/SparkAudio/voxbox.peoples_speech
Dataset Card for People's Speech
Dataset Summary
The People's Speech Dataset is among the world's largest English speech recognition corpus today that is licensed for academic and commercial usage under CC-BY-SA and CC-BY 4.0. It includes 30,000+ hours of transcribed speech in English languages with a diverse set of speakers. This open dataset is large enough to train speech-to-text systems and crucially is available with a permissive license.
Supported Tasks… See the full description on the dataset page: https://huggingface.co/datasets/MLCommons/peoples_speech.yodas2_sidon
YODAS2-Sidon
Overview
This dataset is a cleansed version of YODAS-2 with Sidon speech restoration mode for Speech Synthesis and Spoken Language Modeling.
YODAS-2 is a massive, multilingual YouTube-derived dataset. We have applied the Sidon restoration model to remove background noise and enhance audio quality, making it suitable for high-quality generation tasks.
We resampled original sidon output to 24kHz due to a storage constraints.
The dataset is provided in… See the full description on the dataset page: https://huggingface.co/datasets/sarulab-speech/yodas2_sidon.Multitask-National-Speech-Corpus-v1Multitask-National-Speech-Corpus (MNSC v1) is derived from IMDA's NSC Corpus.
MNSC is a multitask speech understanding dataset derived and further annotated from IMDA NSC Corpus. It focuses on the knowledge of Singapore's local accent, localised terms, and code-switching.
ASR: Automatic Speech Recognition
SQA: Speech Question Answering
SDS: Spoken Dialogue Summarization
PQA: Paralinguistic Question Answering
from datasets import load_dataset
data =… See the full description on the dataset page: https://huggingface.co/datasets/MERaLiON/Multitask-National-Speech-Corpus-v1.unsupervised_peoples_speech
Dataset Card for Unsupervised Peoples Speech
Dataset Description
Dataset Summary
The Unsupervised Peoples Speech Dataset is a compilation of audiofiles extracted from Archive.org that is licensed for academic and commercial usage under CC-BY and CC-BY-SA licenses. It includes more than one million hours of audio with a diverse set of speakers.
Point of Contact: MLCommons Datasets Discord
Dataset Structure
This dataset is a collection of audio… See the full description on the dataset page: https://huggingface.co/datasets/MLCommons/unsupervised_peoples_speech.voicehub-arena-seed-tts-eval
VoiceHub Arena — native TTS evaluations
Incrementally published generated audio and WER, CER, DNSMOS, WavLM-large ECAPA
speaker SIM and UTMOS22 measurements. The full campaign is still running.
Each generation method is evaluated separately using its publisher's native API.
Full evaluations contain all 1,088 English Seed-TTS-Eval targets; eight-target
diagnostic pilots are stored separately and must not be treated as full scores.
Interactive demo ·
Source code
Layout… See the full description on the dataset page: https://huggingface.co/datasets/VoiceHub/voicehub-arena-seed-tts-eval.symile-m3
Dataset Card for Symile-M3
Symile-M3 is a multilingual dataset of (audio, image, text) samples. The dataset is specifically designed to test a model's ability to capture higher-order information between three distinct high-dimensional data types: by incorporating multiple languages, we construct a task where text and audio are both needed to predict the image, and where, importantly, neither text nor audio alone would suffice.
Paper: https://arxiv.org/abs/2411.01053
GitHub:… See the full description on the dataset page: https://huggingface.co/datasets/arsaporta/symile-m3.acidspeech-wikimedia
Dataset Card for Speech Wikimedia
Dataset Summary
The Speech Wikimedia Dataset is a compilation of audiofiles with transcriptions extracted from wikimedia commons that is licensed for academic and commercial usage under CC and Public domain. It includes 2,000+ hours of transcribed speech in different languages with a diverse set of speakers.
Each audiofile should have one or more transcriptions in different languages.
Transcription languages
English
German… See the full description on the dataset page: https://huggingface.co/datasets/MLCommons/speech-wikimedia.SynStard-1000
SynStard-1000
Dataset Summary
SynStard-1000 is a 1,000-hour synthetic dataset for training and evaluating end-to-end speech-to-speech translation (S2ST) models. It is built from English-Chinese parallel texts in the WMT News Commentary v18 corpus and contains approximately 390,000 sentence pairs with paired synthetic speech.
Dataset Structure
.
├── map/
│ └── all.tsv
│── text/
│ ├── en/
│ │ ├── en.txt
│ │ ├── en_1.txt
│ │ ├── ...
│ │ ├──… See the full description on the dataset page: https://huggingface.co/datasets/cksqs/SynStard-1000.gigaspeech
Dataset Card for Gigaspeech
Dataset Description
GigaSpeech is an evolving, multi-domain English speech recognition corpus with 10,000 hours of high quality labeled audio suitable for supervised training. The transcribed audio data is collected from audiobooks, podcasts and YouTube, covering both read and spontaneous speaking styles, and a variety of topics, such as arts, science, sports, etc.
Example Usage
The training split has several configurations of… See the full description on the dataset page: https://huggingface.co/datasets/speechcolab/gigaspeech.SpeechRu
Russian Podcasts (unlabeled)
~186k unlabeled Russian-language podcast episodes scraped from the web,
packaged as Parquet shards with the audio bytes embedded. The audio has no
transcripts — this is an unsupervised / self-supervised audio corpus,
suitable for ASR pre-training, speech-representation learning, TTS data
mining, audio classification, and similar tasks.
Each row contains:
audio — the podcast episode (MP3, mostly 128 kbps / 44.1 kHz stereo),
decoded on-the-fly via the… See the full description on the dataset page: https://huggingface.co/datasets/Sinoosoida/SpeechRu.Complete_Data_Source_100K_HOURS
Multi-Language Audio Collection (100K Hours)
This repository is physically reorganized for Absolute 100% Data Visibility.
🏗️ Global Consolidator
Select your language subset to listen to high-quality waveform audio. All shards from legacy and modern pipelines are automatically routed here.
soundscapesgenshin-voice
Genshin Voice
Genshin Voice is a dataset of voice lines from the popular game Genshin Impact.
Hugging Face 🤗 Genshin-Voice
ModelScope Genshin-Voice
Per-speaker downloads are grouped by language and ZIP size. Browse every archive in the ZIP index.
Last update at 2026-08-13
654252 wavs
7291 without speaker (1%)
52693 without transcription (8%)
1088 without inGameFilename (0%)
Dataset Details
Dataset Description
The dataset contains voice lines… See the full description on the dataset page: https://huggingface.co/datasets/simon3000/genshin-voice.satb-choral-dataset
SATB Choral Source Separation Dataset (Compressed)
This dataset contains preprocessed 4-second audio chunks from the Choral Singing Dataset (CSD) formatted for SATB (Soprano, Alto, Tenor, Bass) voice source separation tasks.
This is the compressed version with 8kHz sample rate and int8 precision for smaller file sizes.
Data Structure
Folder Structure
├── chunks/ # All individual chunk .pt files
├── quality_samples/ # Sample WAV… See the full description on the dataset page: https://huggingface.co/datasets/EwanB/satb-choral-dataset.c-sac-corpora
C-SAC LibriTTS-R training subset
Deterministically selected and resampled speech from
mythicinfinity/libritts_r
for the C-SAC causal speech-codec program. The package retains source revision,
Parquet shard, row, utterance, transcript, and content hashes. LibriTTS-R is
distributed under CC BY 4.0; downstream users remain responsible for attribution.
Only prefixes with a hash-bound _COMPLETE.json sentinel are admissible.
AISHELL-4
AISHELL-4
Identifier: SLR111
Summary: A Free Mandarin Multi-channel Meeting Speech Corpus, provided by Beijing Shell Shell Technology Co.,Ltd
Category: Speech
License: CC BY-SA 4.0
Downloads (use a mirror closer to you):
train_L.tar.gz [7.0G] ( Training set of large room, 8-channel microphone array speech
) Mirrors:
[US]
[EU]
[CN]
train_M.tar.gz [25G] ( Training set of medium room, 8-channel microphone array speech
) … See the full description on the dataset page: https://huggingface.co/datasets/shenyunhang/AISHELL-4.speech_robust_bench
Dataset Card for "speech_robust_bench"
More Information needed
dummy-audio-samplesstg-paired-audioshamupisemantic-vad-eot
Semantic-VAD EOT
End-of-turn (semantic VAD) turns built from word-level forced alignments, schema-compatible
with livekit/eot-bench-data.
Each row is one user turn: an audio clip (16 kHz mp3), its words, and ordered
silence_spans. Per the eot-bench convention the last silence span is the true
end-of-turn (eot); earlier spans are mid-turn hold pauses (labels positional, not stored).
Splits
For every data type, all shards except the last form the train base; that… See the full description on the dataset page: https://huggingface.co/datasets/Scicom-intl/semantic-vad-eot.Vedavani-Dataset
Vedavani: A Benchmark Corpus for ASR on Vedic Sanskrit Poetry
Vedavani is the first benchmark dataset for automatic speech recognition (ASR) on Vedic Sanskrit poetry, consisting of richly annotated verses from the Rig Veda and Atharva Veda. This corpus captures the unique prosodic structure, phonetic complexity, and chanting style found in traditional Vedic recitation.
🔗 Paper: Vedavani: A Benchmark Corpus for ASR on Vedic Sanskrit Poetry (ACL 2025)📁 GitHub Repository:… See the full description on the dataset page: https://huggingface.co/datasets/sanganaka/Vedavani-Dataset.excavationpro-music-stream
Excavationpro public music stream (160 kbps)
Owner / artist: Justin Helmer · Excavationpro · LightfatherPolicy: Own-work only. Public discovery streams (not DistroKid-dependent).Lattice signature: Δ9Φ963-PUBLIC-MUSIC-STREAM-v1
Listen
https://deepseekoracle.github.io/Excavationpro/excavationpro-listen.html
http://asiancoastline.com/ (custom domain music portal)
Layout
Path
Role
stream/<sha256>.mp3
Flat 160k streams (~first 10k −… See the full description on the dataset page: https://huggingface.co/datasets/DeepSeekOracle/excavationpro-music-stream.mls_sidon
MLS-Sidon
Overview
This dataset is a cleansed version of Multilingual LibriSpeech (MLS) with Sidon speech restoration mode for Speech Synthesis and Spoken Language Modeling.
The dataset is provided in WebDataset format for efficient large-scale training.
Source: Multilingual LibriSpeech
Languages: English, German, French, Spanish, Italian, Polish, Dutch, Portuguese
Format: WebDataset (.tar shards)
License: CC-BY-4.0
Dataset Structure
Each sample in… See the full description on the dataset page: https://huggingface.co/datasets/sarulab-speech/mls_sidon.