datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
minds14
MInDS-14
MINDS-14 is training and evaluation resource for intent detection task with spoken data. It covers 14
intents extracted from a commercial system in the e-banking domain, associated with spoken examples in 14 diverse language varieties.
Example
MInDS-14 can be downloaded and used as follows:
from datasets import load_dataset
minds_14 = load_dataset("PolyAI/minds14", "fr-FR") # for French
# to download all data for multi-lingual fine-tuning uncomment following… See the full description on the dataset page: https://huggingface.co/datasets/PolyAI/minds14.Pretraining-V1
Indic TTS Unified v1
A large-scale, unified collection of speech data for text-to-speech (TTS) and speech research. This dataset consolidates 17 distinct source datasets into a single, schema-normalized resource covering Indian / South Asian languages, plus major European, African, MENA, and Central Asian languages, with over 13.7 million utterances and 26,000+ hours of audio.
All audio is resampled to 24 kHz mono. Every row follows an identical schema regardless of source… See the full description on the dataset page: https://huggingface.co/datasets/projectkaira/Pretraining-V1.open-yap-1k
Open Yap 1K: 1,000 hours of full-duplex natural conversation, free for commercial use
Today we're releasing Open Yap 1K: 1,000 hours of dual-channel English conversation, capturing how people speak together naturally in real-world environments recorded in 48kHz. The dataset ships free for both commercial and research use.
The sample on the Hugging Face Hub - 8.9 hours, 16 conversations, CC-BY-4.0, listenable in the dataset viewer.
The full corpus - 1,000 hours, 1,602… See the full description on the dataset page: https://huggingface.co/datasets/TheAgenticDataCompany/open-yap-1k.100-hour-Egyptian-dataset-single-speaker
Masri 100h — Egyptian Arabic Single-Speaker Speech Corpus
A 100-hour Egyptian Arabic (مصري) single-narrator speech collection — 15,653 released clips at 24 kHz mono, with aligned transcripts.
Egyptian Arabic is the most widely understood Arabic dialect and one of the least served by open speech data.
Almost every open Arabic corpus is Modern Standard Arabic (MSA) — a register nobody actually speaks at home.
This dataset is built for the opposite: natural, spoken, conversational… See the full description on the dataset page: https://huggingface.co/datasets/ehabnegm/100-hour-Egyptian-dataset-single-speaker.common-voice-13-faThe Persian portion of the original CommonVoice 13 dataset at https://huggingface.co/datasets/mozilla-foundation/common_voice_13_0
Load
# Using HF Datasets
from datasets import load_dataset
dataset = load_dataset("hezarai/common-voice-13-fa", split="train")
# Using Hezar
from hezar.data import Dataset
dataset = Dataset.load("hezarai/common-voice-13-fa", split="train")
p1-segments
DR P1 speech segments
Dataset
Danish speech clips from DR P1, in mono 16 kHz OGG/Opus, with verbatim text, timing, and speaker metadata. Transcript text and speaker attribution may contain automated errors.
Source
The recordings cover roughly 2006–2022 and come from DR P1 recordings in kb.dk’s DR archive. Audio is sourced through the pinned syvai/p1 revision 449b9c2294026df6d0d37538f279fdec03f565ff. Transcripts were generated with ElevenLabs… See the full description on the dataset page: https://huggingface.co/datasets/syvai/p1-segments.ISSAI_KSC_335RS_v_1_1
Dataset Card for "ISSAI_KSC_335RS_v_1_1"
Kazakh Speech Corpus (KSC)
Identifier: SLR102
Summary: A crowdsourced open-source Kazakh speech corpus developed by ISSAI (330 hours)
Category: Speech
License: Attribution 4.0 International (CC BY 4.0)
Downloads (use a mirror closer to you):
ISSAI_KSC_335RS_v1.1_flac.tar.gz [19G] (speech, transcripts and metadata ) Mirrors: [US] [EU] [CN]
About this resource:
A crowdsourced open-source speech corpus for the Kazakh language. The KSC… See the full description on the dataset page: https://huggingface.co/datasets/Shirali/ISSAI_KSC_335RS_v_1_1.MNV_17
MNV-17: A High-Quality Performative Mandarin Dataset for Nonverbal Vocalization Recognition
Dataset Description
MNV-17 是一个7.55小时的高质量表演式中文语音数据集，专为非语言发声（NV）识别而设计。该数据集解决了NV感知ASR缺乏高质量、标注良好数据集的问题，提供了一个包含17个不同且平衡良好的常见NV类别的语料库。数据集由来自不同地区的中文母语者录制。通过使用脚本化方法，确保每个NV实例都是有意的且清晰的。该数据集旨在促进表达性ASR的未来研究。
MNV-17 is a 7.55-hour high-quality performative Mandarin speech dataset designed for nonverbal vocalization (NV) recognition. It addresses the lack of high-quality, well-annotated datasets… See the full description on the dataset page: https://huggingface.co/datasets/maimai11/MNV_17.cv-v1.0-segment
CommonVoice v1 Phone-Segment Alignments
Phone-level time alignments for 10 languages of Mozilla Common Voice,
packaged in a canonical segmentation schema with embedded 16 kHz audio. The
phone boundaries come from the charsiu/cv_ali
release of MFA alignments; the audio and transcripts come from
Common Voice Corpus 13.0 (2023-03-09).
Dataset summary
lang
train rows
train hrs
val rows
val hrs
test rows
test hrs
en
1,008,669
1,354.0
3,537
4.9
1,285
1.7
rw… See the full description on the dataset page: https://huggingface.co/datasets/changelinglab/cv-v1.0-segment.voiceNam
Dataset Tiếng Việt (Voice Nữ)
Đây là bộ dữ liệu bao gồm file âm thanh và transcript tương ứng, được sử dụng cho việc train mô hình TTS (Text-to-Speech).
Cấu trúc dữ liệu
audio: File âm thanh (.wav)
text: Nội dung văn bản tương ứng
Cách sử dụng
from datasets import load_dataset
dataset = load_dataset("doduy1911/voiceNamNam", split="train")
# Nghe thử mẫu đầu tiên
print(dataset[0]["text"])
t2a-audios-v1
t2a-audios-v1
The original text2asmr corpus (previously aoxo/audios): 48 kHz stereo ASMR audio with word-level
alignments, used for the v1 generator (Chatterbox speech LoRA, Stable Audio Open trigger LoRA) and as
the source for the reconstructed trigger ontology.
Superseded for ontology work by aoxo/t2a-mommy and
aoxo/t2a-daddy, which are larger, creator-attributed
and split by voice.
path
what
<id>.m4a
source audio, 48 kHz
<id>.json
word-level alignment + silence… See the full description on the dataset page: https://huggingface.co/datasets/aoxo/t2a-audios-v1.tarteel-ai-everyayah-Quran﷽
Dataset Card for Tarteel AI's EveryAyah Dataset
Dataset Summary
This dataset is a collection of Quranic verses and their transcriptions, with diacritization, by different reciters.
How to download
!pip install -q datasets
from datasets import load_dataset
dataset =load_dataset("Salama1429/tarteel-ai-everyayah-Quran", verification_mode="no_checks")
Supported Tasks and Leaderboards
[Needs More Information]
Languages
The audio is in… See the full description on the dataset page: https://huggingface.co/datasets/Salama1429/tarteel-ai-everyayah-Quran.BinauralLibriSpeech
Dataset Card for Dataset Name
This is a Binaural version of LibriSpeech, created using HRTFs from the ARI database and reverberation using simulated RIRs from the SLR28 Room Impulse Response and Noise Database.
The dataset has annotations of the source direction as well as microphone array geometry.
Dataset Details
Dataset Description
Curated by: [More Information Needed]
Language(s) (NLP): English
License: [More Information Needed]
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/Holger1997/BinauralLibriSpeech.mls_eng_10k
Dataset Summary
This is a 10K hours subset of English 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. It includes about 44.5K hours of English and… See the full description on the dataset page: https://huggingface.co/datasets/parler-tts/mls_eng_10k.UltiMed-ASR-FR-v1
UltiMed-ASR-FR-v1
A large, fully documented French medical speech dataset for evaluating or training models, plus an open recipe to rebuild it in any language or topic.
Contents
Changelog
What is UltiMed-v1
Why I made UltiMed
Who made UltiMed
Quick start (TL;DR)
How I made UltiMed
Sources
Breakdown by source
Text generation (LLM)
Audio synthesis (TTS)
Hardware and conditions
Repository layout on the Hub
Row format and the two text fields
Loading and training… See the full description on the dataset page: https://huggingface.co/datasets/Olicorne/UltiMed-ASR-FR-v1.Treble10-Speech
Treble10-Speech (16 kHz)
The Treble10-Speech dataset is a dataset for automatic speech recognition (ASR), containing pre-convolved speech files using high fidelity room-acoustic simulations from the Treble10-RIR dataset with 10 different furnished rooms: 2 bathrooms, 2 bedrooms, 2 living rooms with hallway, 2 living rooms without hallway, 2 meeting rooms.
The room volumes range between 14 and 46 m3, resulting in reverberation times between 0.17 and 0.84 s.
Examples:… See the full description on the dataset page: https://huggingface.co/datasets/treble-technologies/Treble10-Speech.IndicSynth
IndicSynth: Indian Multilingual Audio Deepfake Detection & Anti-Spoofing Dataset
A Large-Scale Multilingual Synthetic Speech Dataset for Low-Resource Indian Languages to facilitate audio deepfake detection and anti-spoofing research
🏆 Outstanding Paper Award, ACL 2025
🧠 Overview
IndicSynth is a novel multilingual synthetic speech dataset designed to advance multilingual audio deepfake detection (ADD) and anti-spoofing research. It covers 12 low-resource Indian… See the full description on the dataset page: https://huggingface.co/datasets/mrunmai18/IndicSynth.Galgame_Speech_SER_16kHz
Dataset Card for Galgame_Speech_SER_16kHz
[!IMPORTANT]The following rules (in the original repository) must be followed:
必须遵守GNU General Public License v3.0内的所有协议！附加：禁止商用，本数据集以及使用本数据集训练出来的任何模型都不得用于任何商业行为，如要用于商业用途，请找数据列表内的所有厂商授权（笑），因违反开源协议而出现的任何问题都与本人无关！
训练出来的模型必须开源，是否在README内引用本数据集由训练者自主决定，不做强制要求。
English:
You must comply with all the terms of the GNU General Public License v3.0!Additional note: Commercial use is prohibited. This dataset and any model trained using this dataset… See the full description on the dataset page: https://huggingface.co/datasets/litagin/Galgame_Speech_SER_16kHz.p1
DR P1 Audio Archive
Danish public radio (DR) P1 audio recordings sourced from the kb.dk DR-arkivet (Royal Danish Library DR archive), covering roughly 2006–2022.
Format
Audio: Opus, 24 kbps, mono, in OGG container (transcoded from DR's mp3 archive)
Parquet shards (~500 items each), small row groups for streaming compatibility
Sortable by year / month / start_time
Schema
Each row is one broadcast item with the full audio bytes inline plus rich… See the full description on the dataset page: https://huggingface.co/datasets/syvai/p1.CORAA-v1.1
CORAA-v1.1
CORAA-v1.1 is a publicly available dataset for Automatic Speech Recognition (ASR) in the Brazilian Portuguese language containing 290.77 hours of audios and their respective transcriptions (400k+ segmented audios). The dataset is composed of audios of 5 original projects:
ALIP (Gonçalves, 2019)
C-ORAL Brazil (Raso and Mello, 2012)
NURC-Recife (Oliviera Jr., 2016)
SP-2010 (Mendes and Oushiro, 2012)
TEDx talks (talks in Portuguese)
The audios were either validated by… See the full description on the dataset page: https://huggingface.co/datasets/Racoci/CORAA-v1.1.VieNeu-TTS-140h
pnnbao-ump/VieNeu-TTS-140h
Mô tả Dataset
A high-quality Vietnamese Text-to-Speech (TTS) dataset containing 74,858 audio samples with phonemized transcripts. This benchmark dataset is designed for fine-tuning modern TTS models with maximum synthesis quality. The text corpus is completely phonemized using standard international phonetic alphabet (IPA) representations suitable for neural acoustic modeling.
Quick Facts
Language: Vietnamese 🇻🇳
Tasks:… See the full description on the dataset page: https://huggingface.co/datasets/pnnbao-ump/VieNeu-TTS-140h.ivirits-audio-v2-30s
ivrit.ai audio-v2 — 2–30 s segments
ivrit-ai/audio-v2 (>20k hours of Hebrew
audio) cut into 2–30 second speech segments with machine transcripts, ready for ASR
fine-tuning.
How it was built
VAD — Silero VAD (ONNX) over each episode decoded to 16 kHz mono. Speech regions
longer than 30 s are split at the quietest sufficiently-long pause inside the window,
so cuts land in silence rather than mid-word. Regions shorter than 2 s are dropped.
Transcription —… See the full description on the dataset page: https://huggingface.co/datasets/notmax123/ivirits-audio-v2-30s.KsponSpeechsberdevices_golos_10h_crowd
Dataset Card for sberdevices_golos_10h_crowd
Dataset Summary
Sberdevices Golos is a corpus of approximately 1200 hours of 16kHz Russian speech from crowd (reading speech) and farfield (communication with smart devices) domains, prepared by SberDevices Team (Alexander Denisenko, Angelina Kovalenko, Fedor Minkin, and Nikolay Karpov). The data is derived from the crowd-sourcing platform, and has been manually annotated.
Authors divide all dataset into train and test subsets.… See the full description on the dataset page: https://huggingface.co/datasets/bond005/sberdevices_golos_10h_crowd.composite_corpus_es_v1.0
Composite dataset for Spanish made from public available data
This dataset is composed of the following public available data:
Train split:
The train split is composed of the following datasets combined:
mozilla-foundation/common_voice_18_0/es: "validated" split removing "test_cv" and "dev_cv" split's sentences. (validated split contains official train + dev + test splits and more unique data)
openslr: a train split made from the SLR(39,61,67,71,72,73,74,75,108) subsets… See the full description on the dataset page: https://huggingface.co/datasets/HiTZ/composite_corpus_es_v1.0.Emilia-dataset-french-with-gender
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: [More Information Needed]
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… See the full description on the dataset page: https://huggingface.co/datasets/AdrienB134/Emilia-dataset-french-with-gender.common_voice_19_0_zh-TW
Common Voice Corpus 19.0 Chinese (Taiwan)
The test set is the same as the original test set, while validated_without_test includes all validated examples except those with sentence IDs that appear in the test set.
validated_without_test has about 50,000 examples in total, equivalent to approximately 44 hours, and is intended for use as the training set.
test has about 5,000 examples, which is approximately 5 hours.
vlsp2020_vinai_100h
unofficial mirror of VLSP 2020 - VinAI - ASR challenge dataset
official announcement:
tiếng việt: https://institute.vinbigdata.org/events/vinbigdata-chia-se-100-gio-du-lieu-tieng-noi-cho-cong-dong/
in eglish: https://institute.vinbigdata.org/en/events/vinbigdata-shares-100-hour-data-for-the-community/
VLSP 2020 workshop: https://vlsp.org.vn/vlsp2020
official download: https://drive.google.com/file/d/1vUSxdORDxk-ePUt-bUVDahpoXiqKchMx/view?usp=sharing
contact: info@vinbigdata.org… See the full description on the dataset page: https://huggingface.co/datasets/doof-ferb/vlsp2020_vinai_100h.composite_corpus_eseu_v1.0
Composite bilingual dataset for Spanish and Basque made from public available data
This dataset is composed of the following public available data:
Train split:
The train split is composed of the following datasets combined:
mozilla-foundation/common_voice_18_0/es: a portion of the "validated" split removing "test_cv" and "dev_cv" split's sentences. (validated split contains official train + dev + test splits and more unique data)
mozilla-foundation/common_voice_18_0/eu:… See the full description on the dataset page: https://huggingface.co/datasets/HiTZ/composite_corpus_eseu_v1.0.Galgame_Speech_ASR_16kHz
Dataset Card for Galgame_Speech_ASR_16kHz
[!IMPORTANT]The following rules (in the original repository) must be followed:
必须遵守GNU General Public License v3.0内的所有协议！附加：禁止商用，本数据集以及使用本数据集训练出来的任何模型都不得用于任何商业行为，如要用于商业用途，请找数据列表内的所有厂商授权（笑），因违反开源协议而出现的任何问题都与本人无关！
训练出来的模型必须开源，是否在README内引用本数据集由训练者自主决定，不做强制要求。
English:
You must comply with all the terms of the GNU General Public License v3.0!Additional note: Commercial use is prohibited. This dataset and any model trained using this dataset… See the full description on the dataset page: https://huggingface.co/datasets/litagin/Galgame_Speech_ASR_16kHz.