datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
multilingual-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.multilingual_librispeech
Dataset Card for MultiLingual LibriSpeech
Dataset Summary
This is a streamable version of the Multilingual LibriSpeech (MLS) dataset.
The data archives were restructured from the original ones from OpenSLR to make it easier to stream.
MLS dataset is a large multilingual corpus suitable for speech research. The dataset is derived from read audiobooks from LibriVox and consists of
8 languages - English, German, Dutch, Spanish, French, Italian, Portuguese, Polish.… See the full description on the dataset page: https://huggingface.co/datasets/facebook/multilingual_librispeech.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.MultiTalkFT
MultiTalkFT
Fine-tuning corpus for full-duplex multi-speaker dialogue.
Schemas
data_{zh,en}{,_multichannel}.jsonl (one record per line):
field
type
description
path
string
relative path to the audio file
voice
string
relative path to speaker prompt
duration
float
clip duration in seconds
system
string
persona / system prompt
transcripts/*.parquet:
column
type
description
audio_path
string
matches data_*.jsonl path
idstring
duration… See the full description on the dataset page: https://huggingface.co/datasets/MultiTalk/MultiTalkFT.MultiTalkPT
MultiTalkPT
Pre-training corpus for full-duplex spoken-dialogue models.
Schemas
data_{zh,en}.jsonl (one record per line):
field
type
description
path
string
relative path to the dialogue audio
voice
string
relative path to the speaker prompt audio
duration
float
dialogue duration in seconds
system
string
persona / system prompt
transcripts/*.parquet:
column
type
description
audio_path
string
matches data_*.jsonl path
id
string… See the full description on the dataset page: https://huggingface.co/datasets/MultiTalk/MultiTalkPT.Multitask-National-Speech-Corpus-v1-extendMultiMed-TSSmultilingual_audio_alignments
Multilingual MFA-Aligned Speech Dataset (UNDER DEVELOPMENT)
A large-scale multilingual speech dataset with word-level and phoneme-level alignments produced using the Montreal Forced Aligner (MFA).
Dataset Description
This dataset consolidates multiple speech corpora across various languages, all processed through MFA to provide precise phoneme and word alignments. Each sample includes the original audio, transcript, and detailed timing information for both words and… See the full description on the dataset page: https://huggingface.co/datasets/takuM23/multilingual_audio_alignments.multilingual-speech-commands-3lang-raw
Multilingual Speech Commands Dataset (3 Languages, Raw)
This dataset is a curated subset of previously published speech command datasets in Kazakh, Tatar, and Russian. It is intended for use in multilingual speech command recognition and keyword spotting tasks. No data augmentation has been applied.
All files are included in their original form as released in the cited works below. This repository simply reorganizes them for convenience and accessibility.
Languages… See the full description on the dataset page: https://huggingface.co/datasets/artur-muratov/multilingual-speech-commands-3lang-raw.dnr-v3-multilingualvad-multi-species
Positive Transfer Of The Whisper Speech Transformer To Human And Animal Voice Activity Detection
We proposed WhisperSeg, utilizing the Whisper Transformer pre-trained for Automatic Speech Recognition (ASR) for both human and animal Voice Activity Detection (VAD). For more details, please refer to our paper
Positive Transfer of the Whisper Speech Transformer to Human and Animal Voice Activity Detection
Nianlong Gu, Kanghwi Lee, Maris Basha, Sumit Kumar Ram, Guanghao You, Richard H.… See the full description on the dataset page: https://huggingface.co/datasets/nccratliri/vad-multi-species.open-bible
OpenBibleTTS
OpenBibleTTS is a large-scale, multilingual speech corpus for low-resource text-to-speech (TTS), spanning 37 underrepresented languages across five regions. It contains ~3,469 hours of aligned, verse-level read speech and 1,121,956 utterances, derived from the Open Bible platform and released under a permissive license.
Alignment pipeline: https://github.com/davidguzmanr/open-bible-resources
Source: Open Bible (CC BY-SA)
Languages
Africa (19), South… See the full description on the dataset page: https://huggingface.co/datasets/multilingual-tts/open-bible.multilingual_audio_alignments
Multilingual MFA-Aligned Speech Dataset
A large-scale multilingual speech dataset with word-level and phoneme-level alignments produced using the Montreal Forced Aligner (MFA).
Dataset Description
This dataset consolidates multiple speech corpora across various languages, all processed through MFA to provide precise phoneme and word alignments. Each sample includes the original audio, transcript, and detailed timing information for both words and phonemes.… See the full description on the dataset page: https://huggingface.co/datasets/AAdonis/multilingual_audio_alignments.multispeech_qa
MultispeechQA Dataset
Multilingual spoken-audio question-answering dataset covering 16 languages: Arabic, Czech, German, Greek, French, Hebrew, Hindi, Indonesian, Japanese, Korean, Dutch, Portuguese, Romanian, Spanish, Turkish, Ukrainian. Each example pairs an audio clip with a question and its answer.
Each language config has train / test / validation splits, sharded as multiple .parquet files.
from datasets import load_dataset
ds = load_dataset("your-username/multispeech-qa"… See the full description on the dataset page: https://huggingface.co/datasets/tolulope/multispeech_qa.sib-fleurs-multilingual-miniopen-asr-leaderboard-multilingual-datasets
ASR Leaderboard Datasets
This repository contains test splits from multiple speech corpora, including FLEURS, Common Voice (MCV), and Multilingual LibriSpeech (MLS).
How to Load
To load a specific subset, use load_dataset with the corresponding config_name in the format <set>_<lang>.
from datasets import load_dataset
# Load the FLEURS dataset for Bulgarian
fleurs_bg = load_dataset("nithinraok/asr-leaderboard-datasets", "fleurs_bg")
print(fleurs_bg)
# Load the… See the full description on the dataset page: https://huggingface.co/datasets/hf-audio/open-asr-leaderboard-multilingual-datasets.TTS-Multilingual-Test-Set
Overview
To assess the multilingual zero-shot voice cloning capabilities of TTS models, we have constructed a test set encompassing 24 languages. This dataset provides both audio samples for voice cloning and corresponding test texts.
Specifically, the test set for each language includes:
100 distinct test sentences.
Audio samples from two speakers (one male and one female) carefully selected from the Mozilla Common Voice (MCV) dataset, intended for voice cloning.
Researchers can… See the full description on the dataset page: https://huggingface.co/datasets/MiniMaxAI/TTS-Multilingual-Test-Set.multilingual-TEDX-frThe french subset of the dataset Multilingual TEDx. The data uploaded to HF corresponds to the directory fr-fr. The audio files are automatically resampled to 16 kHz.
Configs:
single_samples (default): all samples taken separately
Sample
{'file': '0u7tTptBo9I-0', 'audio': {'path': None, 'array': array([ 3.05175781e-05, 6.10351562e-05, 9.15527344e-05, ...,
-2.44140625e-04, -3.35693359e-04, -2.74658203e-04]), 'sampling_rate': 16000}, 'sentence': "Bonsoir ! Notre… See the full description on the dataset page: https://huggingface.co/datasets/BrunoHays/multilingual-TEDX-fr.Multimodal_Fish_Feeding_IntensityCSS10-Multilingual-LJSpeech
CSS10-Multilingual-LJSpeech
Multilingual speech dataset combining LJSpeech (English) + CSS10 (10 languages) in a consistent LJSpeech format.
Dataset Description
This dataset merges:
LJSpeech: High-quality English speech dataset
CSS10: A collection of single-speaker speech datasets for 10 languages
All audio files are provided in a consistent format suitable for TTS training.
Features
Each sample contains:
audio: Waveform audio sampled at 22,050 Hz
text:… See the full description on the dataset page: https://huggingface.co/datasets/davidguzmanr/CSS10-Multilingual-LJSpeech.Kartoffelphon-2.5M-de-ger
Kartoffelphon-2.5M-de-ger
Kartoffelphon-2.5M-de-ger is a large-scale German speech dataset built as foundation data for Kartoffel TTS models and related Kartoffel speech projects.
The dataset contains approximately 2.5 million audio-text snippets and an estimated 7,000 hours of speech. The data is mainly German, with some English segments intentionally retained.
Dataset Summary
The dataset is composed mostly of CC / CC-BY based podcast audio, with additional… See the full description on the dataset page: https://huggingface.co/datasets/MultiLlasa/Kartoffelphon-2.5M-de-ger.NEXUS-temporal_hierarchical_multi-modal
NEXUS: Neural Evolution for eXtensible Universal Semantics Dataset
(Temporal Multimodal Slices)
This dataset is a multi-modal, hierarchical, temporal representation derived from HuggingFaceFV/finevideo. It is designed for streaming training where the primary unit is a 10 ms "slice" that aggregates upward into moments (100 ms), seconds (1 s), experiences (10 s), and minutes (60 s).
It is meant to represent an extensible stream of "experience" as there are… See the full description on the dataset page: https://huggingface.co/datasets/Ardea/NEXUS-temporal_hierarchical_multi-modal.marine-animals-multimodal-dataset
Marine Animals Multimodal Dataset 🐋
A comprehensive multimodal dataset combining audio recordings and images of 32 marine species.
Dataset Summary
Total samples: 24,911
Species: 32
Audio files: 1,357 unique recordings
Images: 581 (309 matched + 272 from iNaturalist)
Features
species (string): Species name
label (int32): Numeric label (0–31)
audio (Audio): Audio recording of the species
image (Image): Species image
image_index (int32): Image number… See the full description on the dataset page: https://huggingface.co/datasets/Hariprasath5128/marine-animals-multimodal-dataset.egocentric-vr-capture-20h-multimodal-sample
Egocentric VR Capture — 20-Hour Multimodal Inspection Sample
195 real-world task episodes / 2,283,482 frames / 21.14 delivered hours captured with consumer VR hardware. Each episode combines egocentric RGB and audio with synchronized headset, camera, body, and hand tracking in a LeRobot v3-style package.
This publicly accessible 20-hour-scale dataset is produced by the EXYLOS real-world data pipeline. Files and the Dataset Viewer can be accessed without individual approval;… See the full description on the dataset page: https://huggingface.co/datasets/ExylosAi/egocentric-vr-capture-20h-multimodal-sample.minds14-multilingualmultivsr
Dataset: MultiVSR
We introduce a large-scale multilingual lip-reading dataset: MultiVSR. The dataset comprises a total of 12,000 hours of video footage, covering English + 12 non-English languages. MultiVSR is a massive dataset with a huge diversity in terms of the speakers as well as languages, with approximately 1.6M video clips across 123K YouTube videos. Please check the website for samples.
Download instructions
Please check the GitHub repo to download… See the full description on the dataset page: https://huggingface.co/datasets/sindhuhegde/multivsr.qwen3-tts-multilingual-emotional-speechami-multiscalemixed_multilingual_commonvoice_all_languages_100kBuild from mozilla commonvoice 13 using the script commited in this repo.
Used to teach a model to ignore languages that are not french
common_voice_13_0_bn_multi_split