datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Quranic-Recitation-Data
🌟 Overview
Quranic Recitation Dataset (Word-by-Word Sync) is a highly optimized, production-ready dataset containing high-quality audio recitations of the Holy Quran synchronized at the word-by-word level.
This dataset features 135 world-renowned reciters, with every Surah (114 chapters) mapped precisely to millisecond-accurate word timestamps. It is designed for modern Islamic mobile and web applications — served via a Cloudflare Edge CDN with native… See the full description on the dataset page: https://huggingface.co/datasets/zaibihassan/Quranic-Recitation-Data.MIT_environmental_impulse_responsesMIT Environmental Impulse Response Dataset
The audio recordings in this dataset are originally created by the Computational Audition Lab at MIT. The source of the data can be found at: https://mcdermottlab.mit.edu/Reverb/IR_Survey.html.
The audio files in the dataset have been resampled to a sampling rate of 16 kHz. This resampling was done to reduce the size of the dataset while making it more suitable for various tasks, including data augmentation.
The dataset consists of 271 audio files… See the full description on the dataset page: https://huggingface.co/datasets/davidscripka/MIT_environmental_impulse_responses.YO-CPT-ru
YO-CPT-ru
YouTube-Oriented dataset for Continual Pre-Training (Russian). A large, heavily
quality-filtered corpus of Russian speech mined from YouTube (via YODAS2)
and processed into clean, single-speaker, TTS-grade utterances. Every utterance ships with an
ensemble-verified transcription, a punctuated/denormalized and stress-marked text variant, word-level
forced alignment, within- and cross-video speaker identities, an audio-quality (MOS) score, and a
speaker persona built… See the full description on the dataset page: https://huggingface.co/datasets/NCSpeech/YO-CPT-ru.rixvox-v2
RixVox-v2: A Swedish parliamentary speech dataset
RixVox-v2 is a parliamentary speech dataset spanning nearly 23000 hours of speech. The dataset was built by matching and force aligning speeches in parliamentary protocols to media recordings of debates. Each observation contains metadata about the speaker's name, gender, district, role, party affiliation, and the date the speech was given. We include identifiers for protocols, speeches and speakers that allow linking observations in… See the full description on the dataset page: https://huggingface.co/datasets/KBLab/rixvox-v2.Audio2Tool
Audio2Tool: Speak, Call, Act — A Dataset for Benchmarking Speech Tool Use
Authors: Ramit Pahwa1,∗,∗∗, Apoorva Beedu1,∗, Parivesh Priye1, Rutu Gandhi†1, Saloni Takawale†1, Aruna Baijal1, Zengli Yang1
1 Rivian & Volkswagen Technologies · ∗ equal contribution · ∗∗ corresponding author · † equal contribution
📄 Project page / demo: https://audio2tool.github.io/
📦 Dataset: https://huggingface.co/datasets/RVtech/Audio2Tool
✉️ Contact (corresponding… See the full description on the dataset page: https://huggingface.co/datasets/RVtech/Audio2Tool.Codemixed_New
Codemixed ASR Dataset
Unified collection of code-mixed ASR datasets.
libritts_r_filtered
Dataset Card for Filtered LibriTTS-R
This is a filtered version of LibriTTS-R. It has been filtered based on two sources:
LibriTTS-R paper [1], which lists samples for which speech restoration have failed
LibriTTS-P [2] list of excluded speakers for which multiple speakers have been detected.
LibriTTS-R [1] is a sound quality improved version of the LibriTTS corpus which is a multi-speaker English corpus of approximately
585 hours of read English speech at 24kHz sampling rate… See the full description on the dataset page: https://huggingface.co/datasets/parler-tts/libritts_r_filtered.DeepDialogue-orpheus
DeepDialogue-orpheus
DeepDialogue-orpheus is a large-scale multimodal dataset containing 40,150 high-quality multi-turn dialogues spanning 41 domains and incorporating 20 distinct emotions with coherent emotional progressions. This repository contains the Orpheus variant of the dataset, where speech is generated using Orpheus, a state-of-the-art TTS model that infers emotional expressions implicitly from text.
🚨 Important Notice
This dataset is large (~180GB) due to… See the full description on the dataset page: https://huggingface.co/datasets/SALT-Research/DeepDialogue-orpheus.fma-labeled
FMA Labeled — Multi-Attribute Music Dataset
🏆 Submitted to the Uncharted Data Challenge
hosted by Adaption Labs — credit to
Adaptive Data by Adaption for organizing the hackathon.
A large-scale labeled music dataset built on top of the Creative-Commons
subset of the Free Music Archive (FMA). Every
track has been automatically annotated with lyrics, genre, mood, instruments,
tempo, key, and more using Google Gemini (gemini-flash-latest).
Intended for training and evaluating music… See the full description on the dataset page: https://huggingface.co/datasets/Reubencf/fma-labeled.Galgame-VisualNovel-Reupload
Galgame VisualNovel Reupload
This repository is a reupload of the visual novel dataset OOPPEENN/56697375616C4E6F76656C5F44617461736574.
The goal of this reupload is to restructure the data for easier and more efficient use with the datasets library, instead of having to manually extract each archive file and parse json files of the original dataset.
Loading the entire dataset
To load and stream all voice lines from all games combined, simply load the train split. The… See the full description on the dataset page: https://huggingface.co/datasets/joujiboi/Galgame-VisualNovel-Reupload.RVCBench
RVCBench
RVCBench is a benchmark dataset for studying robustness in voice cloning, text-to-speech, speaker privacy, audio protection, adversarial audio perturbations, and related audio generation pipelines.
Dataset page: https://huggingface.co/datasets/Nanboy/RVCBench
Code repository: https://github.com/Nanboy-Ronan/RVCBench
Paper: https://arxiv.org/abs/2602.00443
RVCBench is designed for evaluating how modern voice cloning (VC), TTS, and audio generation systems behave under… See the full description on the dataset page: https://huggingface.co/datasets/Nanboy/RVCBench.REAL-PS4
REAL-PS4
Overview
REAL-PS4 is a training dataset for target speaker extraction (TSE) and overlapping speech recognition in real-world multi-speaker meetings. It is constructed from four public meeting corpora — AISHELL-4, AliMeeting, AMI, and CHiME-6 — following the REAL-T benchmark data preparation pipeline.
Each sample consists of:
A mixture utterance (overlapping speech clip from a real meeting)
An enrollment utterance (clean speech from the target speaker in… See the full description on the dataset page: https://huggingface.co/datasets/TaurenMountain/REAL-PS4.ytseg
YTSeg: A Benchmark for Audio Chaptering and Video Transcript Segmentation
We present YTSeg, a topically and structurally diverse benchmark for the audio chaptering and transcript segmentation task based on YouTube videos. The dataset comprises 19,299 videos from 393 channels, amounting to 6,533 content hours. The topics are wide-ranging, covering domains such as science, lifestyle, politics, health, economy, and technology. The videos are from various types of content formats… See the full description on the dataset page: https://huggingface.co/datasets/retkowski/ytseg.SUMM-RENote: if the data viewer is not working, use the "example" subset.
SUMM-RE
The SUMM-RE dataset is a collection of transcripts of French conversations, aligned with the audio signal.
It is a corpus of meeting-style conversations in French created for the purpose of the SUMM-RE project (ANR-20-CE23-0017).
The full dataset is described in Hunter et al. (2024): "SUMM-RE: A corpus of French meeting-style conversations".
Created by: Recording and manual correction of the corpus was… See the full description on the dataset page: https://huggingface.co/datasets/linagora/SUMM-RE.tts_farm
Multilingual TTS/ASR Aggregated Dataset
Cleaned, deduplicated and loudness-normalized Arabic, Japanese, Korean, Turkish, and Vietnamese speech. The training columns are audio (16-bit PCM WAV, 22050 Hz) and text; the remaining columns contain quality and provenance metadata.
cantonese-radio
Cantonese Radio Pseudo-Transcription Dataset
Contains 14k hours of audio sourced from Archive.org
Columns
order_index: Represents the order of the audio compared to those from the same filename
link: Link of the original full audio
transcript_whisper: Transcribed using Scrya/whisper-large-v2-cantonese with alvanlii/whisper-small-cantonese for speculative decoding
transcript_sensevoice: Transcribed using FunAudioLLM/SenseVoiceSmall
used OpenCC to convert to traditional chinese… See the full description on the dataset page: https://huggingface.co/datasets/alvanlii/cantonese-radio.gooshkon-chunks
Gooshkon MP3 chunks
A single-column Hugging Face Audio dataset. Every row contains embedded,
playable MP3 bytes in the audio column. Chunks target approximately 30
seconds and are selected at detected quiet intervals with a 12-48 second
safety range.
The source recordings are not transcript-aligned; this release uses acoustic
silence boundaries to avoid cutting through words whenever a usable pause is
available.
Dataset runtime
The dataset contains approximately 2… See the full description on the dataset page: https://huggingface.co/datasets/Reza2kn/gooshkon-chunks.dialogs-ru-emotional-conversations
Dialogs: A Studio-Quality Expressive Conversational Russian Speech Corpus
Dialogs is a 20.6-hour studio-quality corpus of expressive, conversational
Russian speech, designed for dialog-oriented and emotional text-to-speech.
Unlike existing Russian corpora — mostly single-speaker read speech or large but
low-quality web-mined audio — Dialogs was recorded by professional theatre actors
performing scripted dialogs face-to-face, capturing natural turn-taking,
timing, and expressive… See the full description on the dataset page: https://huggingface.co/datasets/langswap/dialogs-ru-emotional-conversations.biggest-ru-bookA bigger version of its5Q/bigger-ru-book, the smaller set being a subset of this one. Almost 1000 hours of high-quality audio.
BERSt
BERSt Dataset
We release the BERSt Dataset for various speech recognition tasks including Automatic Speech Recognition (ASR) and Speech Emotion Recogniton (SER)
Read the paper here
Overview
4526 single phrase recordings (~3.75h)
98 professional actors
19 phone positions
7 emotion classes
3 vocal intensity levels
varied regional and non-native English accents
nonsense phrases covering all English Phonemes
Data collection
The BERSt dataset represents data… See the full description on the dataset page: https://huggingface.co/datasets/Rosie-Lab/BERSt.risale-i-nur-sohbet
Risale-i Nur Sohbet
Prof. Dr. Şener Dilek’ten izin alındı.
Türkçe
Risale-i Nur sohbetlerini ses, ham ASR metni ve zaman hizalı segmentler hâlinde
birlikte sunan bağımsız bir veri kümesidir. İlk sürüm izinli ve doğrulanmış
sohbetleri içerir; kitap metni, grounded, çok dilli veya kitap seslendirme veri
kümelerine karıştırılmaz.
Kapsam
2095 sohbet, 954.66 saat 16 kHz mono FLAC ses
Aynı derslerin ölçülmüş 48 kHz kalite katmanı; 786 derste
seçici… See the full description on the dataset page: https://huggingface.co/datasets/risaleinur/risale-i-nur-sohbet.OmnilingualASR-retrieval
Omnilingual ASR speech-text retrieval (MTEB)
Read speech paired with its human transcription, for languages that no existing
MTEB audio task covers.
Source: facebook/omnilingual-asr-corpus at revision 8648ba8, cc-by-4.0, official
test split. Recordings are re-encoded from FLAC to Opus at 16 kHz. Repeated
transcripts are dropped, since one would otherwise be relevant to several
recordings while only one is marked correct.
Built by… See the full description on the dataset page: https://huggingface.co/datasets/vnahata/OmnilingualASR-retrieval.afvoices
📘 African Next Voices – Bambara (AfVoices)
The AfVoices dataset is the largest open corpus of spontaneous Bambara speech at its release in late 2025. It contains 423 hours of segmented audio and 612 hours of original raw recordings collected across southern Mali. Speech was recorded in natural, conversational settings and annotated using a semi-automated transcription pipeline combining ASR pre-labels and human corrections. We release all the data processing code on GitHub.… See the full description on the dataset page: https://huggingface.co/datasets/RobotsMali/afvoices.Quran-Ayah-Corpus
Quran-Ayah-Corpus: A Multi-Reciter Arabic Quranic Speech Dataset
Dataset Description:
Ayah-Corpus is a large-scale, multi-reciter Arabic speech dataset meticulously curated for Automatic Speech Recognition (ASR) tasks. It consists of high-quality audio recordings of Quranic verses (Ayahs) paired with their corresponding exact transcriptions. The audio is sourced from two primary repositories: Al-Quran.cloud and EveryAyah.com.
This dataset is specifically designed to… See the full description on the dataset page: https://huggingface.co/datasets/rabah2026/Quran-Ayah-Corpus.ravnursson_asr
Dataset Card for ravnursson_asr
Dataset Summary
The corpus "RAVNURSSON FAROESE SPEECH AND TRANSCRIPTS" (or RAVNURSSON Corpus for short) is a collection of speech recordings with transcriptions intended for Automatic Speech Recognition (ASR) applications in the language that is spoken at the Faroe Islands (Faroese). It was curated at the Reykjavík University (RU) in 2022.
The RAVNURSSON Corpus is an extract of the "Basic Language Resource Kit 1.0" (BLARK 1.0) [1] developed… See the full description on the dataset page: https://huggingface.co/datasets/carlosdanielhernandezmena/ravnursson_asr.MyMentorLLM-dataset
Dataset Card for MyMentorLLM
This dataset accompanies the MyMentorLLM paper, arXiv:2607.25667, which describes the simulation environment, generation procedure, experimental design and validation analyses. If you use this dataset, please cite the paper (see Citation Information).
Dataset Summary
MyMentorLLM is a multimodal voice- and text-based deliberate-practice environment used to generate 2,100 simulated Cognitive Behavioural Therapy (CBT) training sessions… See the full description on the dataset page: https://huggingface.co/datasets/RodolfoRizzi/MyMentorLLM-dataset.russian_librispeech
Russian LibriSpeech (RuLS)
Identifier: SLR96 from openslr.org
Summary: This dataset is based on LibriVox audiobooks
Category: Speech
License: The dataset is Public Domain in the USA.
About this resource:
Russian LibriSpeech (RuLS) dataset is based on LibriVox's public domain audio books (see BOOKS.TXT for the list of included books) and contains about 98 hours of audio data.
TIE_shorts
Dataset Card for TIE_Shorts
Dataset Summary
TIE_shorts is a derived version of the Technical Indian English (TIE) dataset, a large-scale speech dataset (~ 8K hours) originally consisting of approximately 750 GB of content
sourced from the NPTEL platform. The original TIE dataset contains around 9.8K technical lectures in English delivered by instructors from various regions across India,
with each lecture averaging about 50 minutes. These lectures cover a wide range of… See the full description on the dataset page: https://huggingface.co/datasets/raianand/TIE_shorts.radiotalk-us-audio-tada-clean
RadioTalk US Audio (Clean)
Synthesized clean-speech audio for ~100k US air-traffic-control conversation scenarios. One row per turn, embedded 24 kHz mono PCM_16 WAV.
This is the clean variant. A VHF-AM-channel-degraded variant is published as twangodev/radiotalk-us-audio-tada-noisy.
Quick start
from datasets import load_dataset
ds = load_dataset("twangodev/radiotalk-us-audio-tada-clean", split="train", streaming=True)
row = next(iter(ds))
print(row["text"]… See the full description on the dataset page: https://huggingface.co/datasets/twangodev/radiotalk-us-audio-tada-clean.radiotalk-us-audio-grok-clean
radiotalk-us-audio-grok-clean
Clean TTS audio for the v3 radiotalk transcripts: one row per transmission,
24 kHz mono PCM_16 WAV. Covers all 49,975 rendered scenarios of
twangodev/radiotalk-us-transcripts-grok-4.20-50k
— 527,701 utterances in uniform 1,250-row shards.
Synthesis: xAI Grok TTS API, 26 preset voices. Each scenario's speakers get
a deterministic voice assignment (seeded by scenario id) and a fixed
per-speaker speaking rate in 1.0–1.3×. 9 scenarios were dropped for… See the full description on the dataset page: https://huggingface.co/datasets/twangodev/radiotalk-us-audio-grok-clean.