datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.hashed_data
Munch Hashed Index - Lightweight Audio Reference Dataset
📖 Overview
Munch Hashed Index is a lightweight reference dataset that provides SHA-256 hashes for all audio files in the Munch Urdu TTS Dataset. Instead of storing 1.27 TB of raw audio, this index stores only metadata and cryptographic hashes, enabling:
✅ Fast duplicate detection across 4.17 million audio samples
✅ Efficient dataset exploration without downloading terabytes
✅ Quick metadata queries (voice… See the full description on the dataset page: https://huggingface.co/datasets/humair025/hashed_data.omnievalkit-dataset
OmniEvalKit Evaluation Datasets
Evaluation datasets for OmniEvalKit,
a comprehensive evaluation framework for omni-modal (audio + video + image + text) models.
Overview
Total subsets: 65
Total samples: 315,264
Total size: 620.3 GB (Parquet with embedded audio/image/video)
Subsets with embedded video: 15
Subsets requiring external video download: 2
Usage
from datasets import load_dataset
ds = load_dataset("OmniEvalKit/omnievalkit-dataset", "aishell1_test")… See the full description on the dataset page: https://huggingface.co/datasets/OmniEvalKit/omnievalkit-dataset.star-wars-dataset
Star Wars dialogue dataset - annotation layers (snapshot 2026-09-21)
One master cue table serving diarization, ASR and dialogue-LLM training: every subtitle cue part of
15 titles with a forced-aligned time span, a character label and provenance. No audio or video is
included - the source media is copyrighted. Clip paths in the manifests resolve once you rebuild the clips
from your own copies with the pipeline code (export_asr.py, export_diarization.py).
The text layers contain… See the full description on the dataset page: https://huggingface.co/datasets/IMJONEZZ/star-wars-dataset.fama-data
Dataset Description, Collection, and Source
The FAMA training data is the collection of English and Italian datasets for automatic speech recognition (ASR) and speech translation (ST)
used to train the FAMA models family.
The ASR section of FAMA is derived from the MOSEL data collection, including the automatic
transcripts obtained with Whisper and available in the HuggingFace MOSEL Dataset.
The ASR is further augmented with automatically transcribed speech from the… See the full description on the dataset page: https://huggingface.co/datasets/FBK-MT/fama-data.skylar-dataset
Skylar Dataset
A curated speech dataset built for automatic speech recognition (ASR)
benchmarking. It is assembled by streaming samples from existing public
audio datasets and keeping only the ones that pass a fixed set of quality
and diversity rules, organized by target language and audio duration.
This is not a single-source dataset: samples are pulled from multiple
upstream datasets into one unified structure. Re-running the pipeline with
a different source (same or different… See the full description on the dataset page: https://huggingface.co/datasets/skylar-ai-hf/skylar-dataset.Indonesian-ASR-11-Class-Dataset
Indonesian ASR 11-Class Dataset
Public Hugging Face repository for an Indonesian ASR corpus and its paper-supporting benchmark artifacts.
Dataset summary
Audio files: 104,500 WAV files
Real/human recordings: 104,368
Synthetic repair files: 132
Sentence classes: 11 Indonesian sentence categories
Canonical balanced sentence slots: 209 (11 categories × 19 retained slots)
Public speaker labels: M1..M12, F1..F8, plus synthetic labels Ms*/Fs*
Audio format: 16 kHz… See the full description on the dataset page: https://huggingface.co/datasets/Atika88/Indonesian-ASR-11-Class-Dataset.pao-audio-dataset
🎙️ Pa'O Audio Dataset
ပအိုဝ်ႏ အငေါဝ်း အဆင်ႏဗာႏ ရွမ်ခြွဉ်းဗူႏ
📌 Project Summary
The Pa'O Audio Dataset is an open-source initiative created to facilitate the development of speech technologies and Artificial Intelligence tools for the Pa'O language (ပအိုဝ်ႏဘာႏသာႏငေါဝ်းငွါ).
Pa'O is primarily spoken in Shan State and other regions of Myanmar. As a low-resource language in the AI landscape, this dataset provides audio recordings and corresponding… See the full description on the dataset page: https://huggingface.co/datasets/paodigitalhub/pao-audio-dataset.ai231-fil-supplemental-data
AI231 ME2 Filipino-accented synthetic commands (supplemental training data)
Optional extra training data for the AI231 ME2 voice-command dataset:
English voice commands spoken by 17 cloned Filipino-accented voices. It follows that dataset's schema and is train only:
it is not part of its train, test or holdout splits.
data/train-0000{0..3}-of-00004.parquet 14,120 clips, 8.7 h, 17 voices, 19 commands (223-1,482 clips each)
Audio: 16 kHz, mono, 16-bit PCM WAV, stored in the… See the full description on the dataset page: https://huggingface.co/datasets/martinnavs/ai231-fil-supplemental-data.korean-full-duplex-synthetic-dataset-preview
Korean Full-Duplex Synthetic Dataset Preview
Overview
Public preview of a Korean full-duplex synthetic speech dataset. This
repository contains 100 conversations sampled from a corpus of 89,273
conversations (2,000.5 hours); it does not publish the full corpus audio.
Preview contents
100 conversation WAV files
data/representative.jsonl
24 kHz, mono, 16-bit PCM
Events: normal, barge_in, backchannel, cutoff_by_user
Annotation format… See the full description on the dataset page: https://huggingface.co/datasets/Wi-Fi/korean-full-duplex-synthetic-dataset-preview.Arabic-Emotional-Audio-Dataset-Baved
BAVED — Basic Arabic Vocal Emotions Dataset (TTS-ready repackaging)
A re-packaged, transcript-aligned version of the Basic Arabic Vocal Emotions Dataset (BAVED) with explicit Arabic transcripts, English glosses, speaker metadata, and speaker-disjoint train/validation/test splits.
Original dataset: Aouf Yacine, Basic Arabic Vocal Emotions Dataset (BAVED), GitHub: https://github.com/40uf411/Basic-Arabic-Vocal-Emotions-Dataset. This repackaging adds metadata; all audio is unchanged.… See the full description on the dataset page: https://huggingface.co/datasets/FatimahEmadEldin/Arabic-Emotional-Audio-Dataset-Baved.Swedia-ASR-Dataset
Swedia ASR Dataset
This repository contains a small Swedish ASR evaluation dataset based on speech
transcriptions from Swedia 2000. It was assembled to compare automatic
speech-recognition output against manually corrected reference transcriptions
for Swedish dialectal speech.
The dataset is useful for quick experiments with Swedish ASR systems, especially
when you want to inspect recognition quality on spontaneous speech from
different regions, speakers, ages, and genders.… See the full description on the dataset page: https://huggingface.co/datasets/kvest/Swedia-ASR-Dataset.kupe-asr-en-data
kupe-asr-en-mini-150m — data
Two loadable configs, packed into ~20-25 bunch_*.parquet files each (Hub-quota friendly):
raw — 24 kHz mono English audio (flac bytes) + text. The encode stage reads this.
mimi — Mimi c0..c7 codes (12.5 Hz) + text. Training reads this.
Ledgers under ledger/ (data.json, mimi.json) track collected/encoded hours and resume state.
from datasets import load_dataset
ds = load_dataset("anuj-inavlabs/kupe-asr-en-data", "mimi", split="train")
sarvam-tts-dataset
Sarvam TTS Dataset: Indian English and Hindi
A curated speech dataset for TTS model training, containing 396 clips in Indian English (en-IN) and Hindi (hi-IN) totalling 57.3 minutes (3440 seconds).
Pipeline source code: https://github.com/Ayush147258/sarvam-tts-dataset
Dataset Summary
Stat
Value
Total clips
396
Total duration
57.3 minutes (3440 seconds)
Clip duration range
5.0s to 26.5s
Mean clip duration
8.7s
Median clip duration
7.5s… See the full description on the dataset page: https://huggingface.co/datasets/ayush712145/sarvam-tts-dataset.ktt-math-tutor-data
KTT Math Tutor — Data
Data artefacts for the AIMS KTT Hackathon Tier-3 submission
S2.T3.1 AI Math Tutor for Early Learners. Source code:
https://github.com/DrUkachi/ktt-math-tutor.
Contents
T3.1_Math_Tutor/
Core curriculum + seeds.
curriculum.json — 80 items × 5 sub-skills (counting, number
sense, addition, subtraction, word problem) with EN / FR / KIN
stems, difficulty 1–10, age bands 5–6 / 6–7 / 7–8 / 8–9, visual
asset keys, expected integer answer.… See the full description on the dataset page: https://huggingface.co/datasets/DrUkachi/ktt-math-tutor-data.Processed_TTS_Multilingual_Data
Processed TTS Multilingual Data
Validated and quality-checked multilingual speech datasets for TTS training, covering 12+ Indian languages.
Datasets Included
Subset
Samples
Hours
Description
indic_voices_r
239,684
548.8h
Indic Voices_R — IVR recordings
rasa
201,509
361.2h
RASA — read speech (wiki, conv, book, news)
indictts_iitm
155,236
253.6h
Indic TTS (IIT Madras) — studio TTS recordings at 48kHz
Total
596,429
1,163.6h
Languages… See the full description on the dataset page: https://huggingface.co/datasets/PalakEngineerMaster/Processed_TTS_Multilingual_Data.Trump_Voice_Dataset
Trump Voice Dataset
This dataset contains audio clips of Donald Trump's speech from the World Economic Forum (WEF) 2018, paired with their corresponding transcriptions. The dataset is designed for text-to-speech (TTS) and speech recognition tasks.
Dataset Description
Dataset Summary
The Trump Voice Dataset consists of 20 audio samples (10 train, 10 test) extracted from Donald Trump's speech at the World Economic Forum 2018. Each audio clip is approximately 10… See the full description on the dataset page: https://huggingface.co/datasets/Sakchham19/Trump_Voice_Dataset.stage1a_smoke_data
stage1a_smoke_data — AuT-ready 128-mel TFRecords (en/zh)
Smoke-scale training data for Stage 1A input audio alignment of a Qwen3-ASR-AuT → MLP →
frozen-VL-LLM omni model. Audio is pre-extracted 128-bin log-mel (the Qwen3-ASR AuT frontend:
WhisperFeatureExtractor, 16 kHz, hop 160, n_fft 400) so training only needs to run the frozen AuT
encoder — no raw-audio decoding at train time.
113,396 samples across 4 sources, stored as GZIP-compressed TFRecords (one file per source shard).… See the full description on the dataset page: https://huggingface.co/datasets/Letian2003/stage1a_smoke_data.egyptian-arabic-stt-data
Egyptian Arabic STT Dataset
Synthetic Egyptian Arabic speech dataset generated by the
Synthetic Egyptian Speech Data Pipeline.
Samples are human-reviewed and quality-validated using Whisper ASR (WER/CER).
Dataset Statistics
Metric
Value
Total samples
50
Total duration
85.2s (0.02h)
Dialect validated
50 / 50
Average WER
0.4136
Average CER
0.1642
Topics
food_ordering
Fields
Field
Type
Description
id
string
Deterministic… See the full description on the dataset page: https://huggingface.co/datasets/Khaledtelbahnasy/egyptian-arabic-stt-data.welsh-speech-dataset
Welsh Speech Dataset
A multimodal dataset of 33 speakers producing 10 Welsh phrases, captured using 3DMD technology with audio and dense facial landmark annotations.
Dataset Overview
Speakers: 33 participants
Phrases: 10 Welsh phrases per speaker
Sequences: ~330 (33 speakers x 10 phrases)
Modalities:
Audio recordings (.wav)
3D facial reconstructions (.obj meshes + texture maps)
68-point facial landmarks (ibug68 template)
Fluency Scores: Each phrase rated 0-5… See the full description on the dataset page: https://huggingface.co/datasets/Pedramebd/welsh-speech-dataset.welsh-speech-dataset
Welsh Speech Dataset
A multimodal dataset of 33 speakers producing 10 Welsh phrases, captured using 3DMD technology with audio and dense facial landmark annotations.
Dataset Overview
Speakers: 33 participants
Phrases: 10 Welsh phrases per speaker
Sequences: ~330 (33 speakers x 10 phrases)
Modalities:
Audio recordings (.wav)
3D facial reconstructions (.obj meshes + texture maps)
68-point facial landmarks (ibug68 template)
Fluency Scores: Each phrase rated 0-5 (5 =… See the full description on the dataset page: https://huggingface.co/datasets/arvinsingh/welsh-speech-dataset.