datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
yodas-granary
Dataset Card for YODAS-Granary
Repository: NeMo-speech-data-processor: Granary
Paper: Granary: Speech Recognition and Translation Dataset in 25 European Languages
Shared by: ESPnet
Dataset Description
YODAS-Granary is a curated subset of the larger nvidia/Granary dataset, focusing on high-quality pseudo-labeled speech data for Automatic Speech Recognition (ASR) and Automatic Speech Translation (AST) across 23 European languages.
Overview… See the full description on the dataset page: https://huggingface.co/datasets/espnet/yodas-granary.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.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.tat_youtubeopen-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.emilia-yodasA mirror of the Emilia-YODAS dataset. Only includes the YODAS subset from the original dataset.
https://huggingface.co/datasets/amphion/Emilia-Dataset
yt-danish-public-v2ytseg
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.Multi-Talker-SD
Dataset Card for Multi-Talker-SD
Dataset Description
Multi-Talker-SD is a large-scale bilingual (English–Mandarin) multi-speaker meeting dataset designed to support research on speaker diarization and meeting transcription.
Size: 1,000 simulated meetings
Participants per meeting: 10–30 speakers
Average duration: ~20 minutes per meeting, up to one hour
Languages: English, Mandarin (code-switching possible)
Audio characteristics: realistic speaker overlap… See the full description on the dataset page: https://huggingface.co/datasets/yihao005/Multi-Talker-SD.YO-CPT-kk
YO-CPT-kk
YouTube-Oriented dataset for Continual Pre-Training (Kazakh). A heavily
quality-filtered corpus of Kazakh speech mined from YouTube 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 from the
voice and, where… See the full description on the dataset page: https://huggingface.co/datasets/NCSpeech/YO-CPT-kk.pseudolabel-malaysian-youtube-whisper-large-v3
Pseudolabel Malaysian Youtube videos using Whisper Large V3
Original dataset at https://huggingface.co/datasets/malaysia-ai/crawl-youtube, distributed pseudolabelled using 4x A100s
script at https://github.com/mesolitica/malaysian-dataset/tree/master/speech-to-text-semisupervised/pseudolabel-whisper
Each audio is 30 seconds.
Each audio saved in 16k sample rate.
audiobooks170 hours of aligned audiobooks taken from tatkniga.ru. There are 4 speakers with 17+ hours of audio and 20 speakers in total. All the books are in free access and most of them in public domain.
cantonese-youtube-tts
Cantonese Audio TTS Dataset
This dataset contains alvanlii/cantonese-radio, alvanlii/cantonese-youtube, plus a dataset of equal size. It is catered towards TTS (text-to-speech) use cases, more than the 2 previously published datasets, as there is more extensive filtering and audio enhancement. For speaker labelling, you can use speaker embedding models like Nvidia's TitaNet
Filtered out:
Overlapped voices, detected using pyannote/speaker-diarization-3.1
Music, detected using a… See the full description on the dataset page: https://huggingface.co/datasets/alvanlii/cantonese-youtube-tts.yodas-ja000
YODAS Japanese (ja000)
Japanese manual caption subset of the YODAS dataset, repackaged for easier use.
Source
Original dataset: espnet/yodas (ja000 config)
Paper: YODAS: YouTube-Oriented Dataset for Audio and Speech
License: CC BY 3.0
Citation
If you use this dataset, please cite the original YODAS paper:
audiobooks-xxlfleurs
FLEURS
Fleurs is the speech version of the FLoRes machine translation benchmark.
We use 2009 n-way parallel sentences from the FLoRes dev and devtest publicly available sets, in 102 languages.
Training sets have around 10 hours of supervision. Speakers of the train sets are different than speakers from the dev/test sets. Multilingual fine-tuning is
used and ”unit error rate” (characters, signs) of all languages is averaged. Languages and results are also grouped into seven… See the full description on the dataset page: https://huggingface.co/datasets/yohannabelay/fleurs.YouTube-Commons-nl-audio
YouTube Commons NL Audio
This dataset has audio files for the Dutch-language videos in Rijgersberg/YouTube-Commons-nl-transcriptions,
all under a CC BY 4.0 license.
It contains 11,669 files for a total runtime of 2493h 43m 5s, coming in at approximately 130 GB.
Source
The original source of the dataset (minus the titles, descriptions and audio files) is YouTube Commons:
YouTube-Commons is a collection of audio transcripts of 2,063,066 videos shared on YouTube… See the full description on the dataset page: https://huggingface.co/datasets/Rijgersberg/YouTube-Commons-nl-audio.WaxalNLP
Waxal Datasets
The WAXAL dataset is a large-scale multilingual speech corpus for African languages, introduced in the paper WAXAL: A Large-Scale Multilingual African Language Speech Corpus.
Dataset Description
The Waxal project provides datasets for both Automated Speech Recognition (ASR)
and Text-to-Speech (TTS) for African languages. The goal of this dataset's
creation and release is to facilitate research that improves the accuracy and
fluency of speech and… See the full description on the dataset page: https://huggingface.co/datasets/youvoi/WaxalNLP.cantonese-youtube
Cantonese Youtube Pseudo-Transcription Dataset
Contains approximately 10k hours of audio sourced from YouTube
Videos are chosen at random, and scraped on a channel basis
Includes news, vlogs, entertainment, stories, health
Columns
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-youtube.news_youtube_uzbek_speech_dataset
News Youtube Uzbek Speech Dataset
Dataset Description
This dataset contains audio clips and their corresponding transcriptions in the Uzbek language with differenent dialects. The data was collected from publicly available news videos on YouTube. It is designed for training and evaluating Automatic Speech Recognition (ASR) models.
Most of the content comes from the Kunuz, Qalampir YouTube channels. The data was transcribed using Gemini 2.5 Pro and was intelligently… See the full description on the dataset page: https://huggingface.co/datasets/islomov/news_youtube_uzbek_speech_dataset.yoruba-speech-text-parallel
Yoruba Speech-Text Parallel Dataset
Dataset Description
This dataset contains 1647022 parallel speech-text pairs for Yoruba, a language spoken primarily in Nigeria and other West African countries. The dataset consists of audio recordings paired with their corresponding text transcriptions, making it suitable for automatic speech recognition (ASR) and text-to-speech (TTS) tasks.
Dataset Summary
Language: Yoruba - yo
Task: Speech Recognition, Text-to-Speech… See the full description on the dataset page: https://huggingface.co/datasets/michsethowusu/yoruba-speech-text-parallel.youtube_transcriptions
Dataset Description
A speech dataset of Uzbek language audio clips sourced from YouTube videos. Audio segments were extracted, separated by speaker using vocal isolation, and transcribed using Google's Gemini 2.0 Flash model. Speaker identities were clustered using ECAPA-TDNN embeddings.
Use Cases
Automatic Speech Recognition (ASR) for Uzbek
Text-to-Speech (TTS) synthesis for Uzbek
Fine-tuning speech models on Uzbek language data (e.g., Qwen3-TTS)
Speaker-conditioned TTS… See the full description on the dataset page: https://huggingface.co/datasets/openbank-uz/youtube_transcriptions.YouTube-Cantonese
Cantonese Audio Dataset from YouTube
This dataset contains Cantonese audio segments and creator uploaded transcripts (likely higher quality) extracted from various YouTube channels, along with corresponding transcript metadata. The data is intended for training automatic speech recognition (ASR) models.
Data Source and Processing
The data was obtained through the following process:
Download: Audio (.m4a) and available Cantonese subtitles (.srt for zh-TW, zh-HK, zh-Hant)… See the full description on the dataset page: https://huggingface.co/datasets/OrcinusOrca/YouTube-Cantonese.yodas2
YODAS2 for 🇺🇦 Ukrainian
Ukrainian validated subset of YODAS2
Community
Discord: https://bit.ly/discord-uds
Speech Recognition: https://t.me/speech_recognition_uk
Speech Synthesis: https://t.me/speech_synthesis_uk
Stats
Total files processed: 400213
Total duration: 998h 41m 3s
yodas2_sidon_th_tts
Thai TTS Dataset — Filtered & Quality-Verified from YODAS2 sidon
A filtered, quality-verified Thai text-to-speech dataset derived from sarulab-speech/yodas2_sidon, with transcriptions verified by multiple ASR models and Gemini, text fully normalized to Thai, and audio quality-screened with DNSMOS.
Dataset Summary
Samples
141,927
Audio hours
156.0
Speakers
4,199
Sample rate
24,000 Hz
Format
WAV, PCM 16-bit, mono
Language
Thai
Source… See the full description on the dataset page: https://huggingface.co/datasets/Chalermdej/yodas2_sidon_th_tts.EUbookshop-Speech-Irish
Dataset Details
Synthetic audio dataset, created using Azure text-to-speech service.
The bilingual text is a portion of the EUbookshop dataset, consisting of 33,634 text segments.
The dataset includes two sets of audio data, one with a female voice (OrlaNeural) and the other with a male voice (ColmNeural).
The speech data comprises approximately 159 hours and 45 minutes (159:45:05) spread across 67,268 utterances.
Dataset Structure
Dataset({
features: ['audio'… See the full description on the dataset page: https://huggingface.co/datasets/ymoslem/EUbookshop-Speech-Irish.speechio_test
SpeechIO ASR Test Sets (parquet)
Parquet repackaging of the SpeechColab SpeechIO Mandarin ASR benchmark,
re-exported from yuekai/speechio (Lhotse cuts) into standard
HuggingFace parquet with embedded 16 kHz audio.
27 test sets: SPEECHIO_ASR_ZH00000 ... SPEECHIO_ASR_ZH00026, each a config with a single test split.
~43k utterances, ~66 hours total, evaluation only.
Columns
column
type
note
segment_id
string
utterance id
speaker
string
speaker id… See the full description on the dataset page: https://huggingface.co/datasets/yuekai/speechio_test.it_youtube_uzbek_speech_dataset
IT Uzbek Speech Dataset
Dataset Description
This dataset contains audio clips and their corresponding transcriptions in the Uzbek language and with some english to better generalization. The data was collected from publicly available videos on YouTube related to the Information Technology (IT) field. It is designed for training and evaluating Automatic Speech Recognition (ASR) models.
Most of the content comes from the Mohir Dev YouTube channel (respect to the team for… See the full description on the dataset page: https://huggingface.co/datasets/islomov/it_youtube_uzbek_speech_dataset.podcasts_tashkent_dialect_youtube_uzbek_speech_dataset
Tashkent dialect focused podcasts youtube uzbek speech
Dataset Description
This dataset contains audio clips and their corresponding transcriptions in the Uzbek language with mostly tashkent dialects. The data was collected from publicly available podcast videos on YouTube. It is designed for training and evaluating Automatic Speech Recognition (ASR) models.
Most of the content comes from the Jahongir Latipov interviews and Bu podcast (respect authors) YouTube videos. The… See the full description on the dataset page: https://huggingface.co/datasets/islomov/podcasts_tashkent_dialect_youtube_uzbek_speech_dataset.whisper-dataset-ytb-uk
Dataset Card for Dataset Name
This dataset is collected from youtube.