datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Emilia-Dataset
Emilia: An Extensive, Multilingual, and Diverse Speech Dataset for Large-Scale Speech Generation
This is the official repository 👑 for the Emilia dataset and the source code for the Emilia-Pipe speech data preprocessing pipeline.
News 🔥
2025/02/26: The Emilia-Large dataset, featuring over 200,000 hours of data, is now available!!! Emilia-Large combines the original 101k-hour Emilia dataset (licensed under CC BY-NC 4.0) with the brand-new 114k-hour Emilia-YODAS… See the full description on the dataset page: https://huggingface.co/datasets/amphion/Emilia-Dataset.soundscapesLAION-Audio-300MDuplexConv
DuplexConv
DuplexConv is a large-scale Chinese multi-channel conversational speech dataset with LLM-assisted annotations, developed by ASLP@NPU and QualiaLabs as part of the SmoothConv–DuplexConv corpus family.
Companion dataset: SmoothConv on HuggingFace (100 hours, expert human annotation). DuplexConv and SmoothConv share the same conversational domains and a unified data design. SmoothConv focuses on high-quality human annotations for benchmarking and… See the full description on the dataset page: https://huggingface.co/datasets/qualialabsAI/DuplexConv.gigaspeech2
Dataset Card for GigaSpeech 2
Dataset Description
GigaSpeech 2 is an evolving, large-scale, multi-domain, and multilingual ASR corpus focusing on low-resource languages. GigaSpeech 2 raw comprises about 30,000 hours of automatically transcribed speech, across Thai, Indonesian, and Vietnamese. GigaSpeech 2 refine consists of 10,000 hours of Thai, 6,000 hours each for Indonesian and Vietnamese.
Repository: https://github.com/SpeechColab/GigaSpeech2
Paper:… See the full description on the dataset page: https://huggingface.co/datasets/speechcolab/gigaspeech2.laions_got_talent
LAION's Got Talent: Generated Voice Acting Dataset
Overview
"LAION's Got Talent" is a generated dataset comprising voice acting samples that exhibit a wide range of emotions, vocal bursts, topics, and content. This dataset is a component of the BUD-E project, spearheaded by LAION with support from Intel.
Dataset Composition
The dataset includes:
Emotional Diversity: Samples portraying various emotions to facilitate research in emotional recognition and… See the full description on the dataset page: https://huggingface.co/datasets/laion/laions_got_talent.voxlingua107_wds
VoxLingua107
VoxLingua107 is a speech dataset for training spoken language identification models.
The dataset consists of short speech segments automatically extracted from YouTube videos and labeled according the language of the video title and description, with some post-processing steps to filter out false positives.
VoxLingua107 contains data for 107 languages. The total amount of speech in the training set is 6628 hours.
The average amount of data per language is 62 hours.… See the full description on the dataset page: https://huggingface.co/datasets/TalTechNLP/voxlingua107_wds.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.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.reazonspeechaudiosnippetslaion-audio-previewvoxbox
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.emilia-yodasA mirror of the Emilia-YODAS dataset. Only includes the YODAS subset from the original dataset.
https://huggingface.co/datasets/amphion/Emilia-Dataset
Emilia-YODAS-ENClotho-Moment
Clotho-Moment
This repository provides wav files used in Language-based Audio Moment Retrieval.
Each sample includes long audio containing some audio events with the temporal and textual annotation.
Project page: https://h-munakata.github.io/Language-based-Audio-Moment-Retrieval/
Code: https://github.com/line/lighthouse
Split
Train
train/train-{000..715}.tar
37930 audio samples
Valid
valid/valid-{000..108}.tar
5741 audio samples
Test
test/test-{000..142}.tar
7569… See the full description on the dataset page: https://huggingface.co/datasets/lighthouse-emnlp2024/Clotho-Moment.laions_got_talent_rawdns5-16k
DNS5 16kHz
Resampled subset of the ICASSP 2022 DNS Challenge dataset.
All audio files resampled from 48kHz to 16kHz and stored as FLAC (lossless compression),
packed into tar shards.
Structure
clean/shard_0000.tar # Clean speech (VCTK and other corpora)
clean/shard_0001.tar
...
noise/shard_0000.tar # Environmental noise (AudioSet, Freesound)
...
impulse_responses/shard_0000.tar # Room impulse responses
...
Each tar contains FLAC files with their… See the full description on the dataset page: https://huggingface.co/datasets/richiejp/dns5-16k.ASMR-Archive-Processed-SFW
ASMR-Archive-Processed-SFW
Overview
This dataset is an “educational” subset of the original OmniAICreator/ASMR-Archive-Processed dataset.
We filtered the original dataset to include only records where the nsfw metadata flag is false.
To maintain the randomness and anonymity of the entries, multiple directories were combined and shuffled.
The nsfw tag in the original dataset is inherited from the tags of the original audio works before they were passed through the… See the full description on the dataset page: https://huggingface.co/datasets/noxwano/ASMR-Archive-Processed-SFW.mls_hq_urgent_track1audiosnippets_small_with_detailed_annotationvoice-data
Voice-Data: a curated multi-corpus voice dataset for voice–text contrastive training
voice-data is a single, globally-shuffled WebDataset that bundles several voice/speech corpora into one ready-to-train mixture for voice–text contrastive (CLAP-style) models such as VoiceCLAP. Each clip pairs 48 kHz mono FLAC audio with a natural-language text caption describing the voice — its emotion, prosody, timbre, speaking style, recording context, and speaker traits.
The distinguishing… See the full description on the dataset page: https://huggingface.co/datasets/gijs/voice-data.emo_parlercommonvoice22_sidon
CV22-Sidon
Overview
This dataset hosts a release of Mozilla Common Voice 22 restored with the Sidon speech restoration model.
Source: Mozilla Common Voice 22.0
Processing: Sidon denoising (sarulab-speech/sidon-v0.1) with 21 s chunks and 48 kHz reconstruction
Format: WebDataset shards (.tar.gz)
Manifest: paths.yaml enumerates every shard path for Hugging Face–style loading
License: Original Common Voice license (CC0 1.0)
Languages
137 language folders are… See the full description on the dataset page: https://huggingface.co/datasets/sarulab-speech/commonvoice22_sidon.Emolia
Dataset Card for Emolia
Dataset Description
This dataset is an enhanced version of the Emilia dataset, enriched with detailed emotion annotations. The annotations were generated using models from the EmoNet suite to provide deeper insight into the emotional content of speech. This work is based on the research and models described in the blog post "Do They See What We See?".
The annotations include 54 scores for each sample, covering a wide range of emotional and… See the full description on the dataset page: https://huggingface.co/datasets/laion/Emolia.captioned-ai-music-snippets
Dataset Overview
A collection of short audio snippets (3–30 seconds) extracted from publicly shared Suno‑generated songs and captioned with Gemini Flash 2.0. Designed specifically to train and evaluate audio captioning models.
Source
Clips are randomly cut from the songs referenced in the nyuuzyou/suno repository.
Captioning
All excerpts have been annotated using Gemini Flash 2.0 for high‑quality, human‑readable audio descriptions.
License
Apache 2.0
audiosnippets_small_with_detailed_annotation2commonvoice22-sidon-dacvae
CommonVoice 22 (Sidon-enhanced) converted to DAC VAE latents
Source
sarulab-speech/commonvoice22_sidon
Format
Each tar shard (~2GB) contains samples with three files per sample:
{sample_key}.audio.flac # Original audio (FLAC, original sample rate)
{sample_key}.dacvae.npy # DAC VAE latent [T_latent, 128] numpy float32
{sample_key}.metadata.json # All metadata + duration_seconds + chars_per_second
DAC VAE Latent Format
Model:… See the full description on the dataset page: https://huggingface.co/datasets/TTS-AGI/commonvoice22-sidon-dacvae.majestrino-dataemo_webds_2