datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
genshin-voice-v3.3-mandarin
Dataset Card for Genshin Voice
Dataset Description
Dataset Summary
The Genshin Voice dataset is a text-to-voice dataset of different Genshin Impact characters unpacked from the game.
Languages
The text in the dataset is in Mandarin.
Dataset Creation
Source Data
Initial Data Collection and Normalization
The data was obtained by unpacking the Genshin Impact game.
Who are the source language producers?
The… See the full description on the dataset page: https://huggingface.co/datasets/hanamizuki-ai/genshin-voice-v3.3-mandarin.everyayah﷽
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.
Supported Tasks and Leaderboards
[Needs More Information]
Languages
The audio is in Arabic.
Dataset Structure
Data Instances
A typical data point comprises the audio file audio, and its transcription called text.
The duration… See the full description on the dataset page: https://huggingface.co/datasets/tarteel-ai/everyayah.ZeroSpeech
ZeroSpeech
A large synthetic Vietnamese speech corpus for ASR training: 9,867,987
utterances / 26,896 hours, spoken by 199,265
distinct voices, generated with
ZeroTTS from web and
conversational text.
Every clip is 16 kHz mono FLAC, 1–30 s, paired with the exact text it was
synthesized from.
Fields
field
type
description
audio
Audio(16 kHz)
the waveform, FLAC-encoded
text
string
the transcript — the exact string given to the TTS
source
string
which… See the full description on the dataset page: https://huggingface.co/datasets/zeroweight-ai/ZeroSpeech.Neyshekar
Neyshekar
Neyshekar is an open, community-driven Persian speech dataset collected via a web-based crowdsourcing platform at https://ney.shekar.io. It is designed to support research and development in text-to-speech (TTS), automatic speech recognition (ASR), speech representation learning, and other downstream Persian speech applications.
The recordings are provided by volunteer contributors, all of whom are native Persian speakers. Each release represents a… See the full description on the dataset page: https://huggingface.co/datasets/shekar-ai/Neyshekar.synthetic_dem
Dataset Card for synthetic_dem
Dataset Summary
The Synthetic DEM Corpus is the result of the first phase of a collaboration between El Colegio de México (COLMEX) and the Barcelona Supercomputing Center (BSC).
It all began when COLMEX was looking for a way to have its Diccionario del Español de México (DEM), which can be accessed online, include the option to play each of its words with a Mexican accent through synthetic speech files. On the other hand, BSC is always on… See the full description on the dataset page: https://huggingface.co/datasets/projecte-aina/synthetic_dem.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.genshin-voice-v3.5-mandarin
Dataset Card for Genshin Voice
Dataset Description
Dataset Summary
The Genshin Voice dataset is a text-to-voice dataset of different Genshin Impact characters unpacked from the game.
Languages
The text in the dataset is in Mandarin.
Dataset Creation
Source Data
Initial Data Collection and Normalization
The data was obtained by unpacking the Genshin Impact game.
Who are the source language producers?
The… See the full description on the dataset page: https://huggingface.co/datasets/hanamizuki-ai/genshin-voice-v3.5-mandarin.thai-aligner-bench
Thai Aligner Bench
🚧 Development in progress.
How accurately can a forced aligner place Thai token and word boundaries in
speech? This is a self-contained benchmark: one Python file
(aligner_bench.py) plus 1,572 clips of Thai speech with frame-exact timing
ground truth. No Thai NLP stack or other code is needed — just
numpy soundfile torch torchaudio transformers.
The ground truth is what makes the dataset useful: the audio was rendered by a
TTS model whose duration predictor… See the full description on the dataset page: https://huggingface.co/datasets/wayu-ai/thai-aligner-bench.STEAK
STEAK — Speech-to-Text for Error of Atc readbacK
STEAK is a synthetically generated dataset of ATCO–pilot radio exchanges
— both the text and the audio are synthetic:
Text: assembled by formal rules, following an ontology of ATCO–pilot
exchanges.
Audio: TTS → voice timbre / accent conversion (seed-vc) →
noise addition (noise captured from real ATCO2 recordings).
One row = one audio (one ATCO controller utterance or one pilot readback).
2,519,694 audios. The ATCO↔pilot pair is… See the full description on the dataset page: https://huggingface.co/datasets/DEEL-AI/STEAK.voice-code-bench
VoiceCodeBench
VoiceCodeBench is a test-only benchmark for evaluating whether automatic
speech recognition (ASR) systems preserve exact structured values in English
workplace speech.
Paper: VoiceCodeBench: Evaluating Exact Structured-Token Recovery in Automatic Speech Recognition
The benchmark targets cases where a transcript is software input: callback
numbers, email addresses, command-line flags, file paths, URLs, account
identifiers, dates, measurements, and similar values… See the full description on the dataset page: https://huggingface.co/datasets/besimple-ai/voice-code-bench.ASR_Code_Switch
ASR Code-Switching Benchmark
A curated benchmark of 1,200 code-switching utterances (300 per language pair)
for evaluating commercial ASR systems on multilingual speech with intra-sentential
language switching.
Paper
Benchmarking Commercial ASR Systems on Code-Switching Speech: Arabic, Persian, and German
arXiv link
Language pairs
Split
Language pair
Samples
Scripts
egyptian_arabic_english
Egyptian Arabic–English
300
Arabic + Latin… See the full description on the dataset page: https://huggingface.co/datasets/Perle-ai/ASR_Code_Switch.Redmond-Sentence-Recall
Dataset Summary
The Redmond Sentence Recall (RSR) measures a child’s ability to repeat sentences that contain regular past tense forms and past participle forms (e.g., “He kicked” vs. “He was kicked”). This task helps identify language impairments, with each child repeating 16 sentences heard through headphones. The dataset includes anonymized audio recordings of these repetitions.
What makes the RSR dataset uniquely valuable is its focus on sentence recall using both regular past… See the full description on the dataset page: https://huggingface.co/datasets/ai4exceptionaled/Redmond-Sentence-Recall.hailuo-ai-voices
Hailuo AI Voices Dataset 🎤
A curated collection of high-quality voice recordings with corresponding transcriptions and phoneme analysis. This dataset is designed for speech recognition, text-to-speech, and voice analysis tasks.
📊 Dataset Overview
The dataset provides a comprehensive collection of voice samples with the following features:
Feature
Description
Audio Files
High-quality WAV format recordings
Transcription
Accurate transcriptions of each… See the full description on the dataset page: https://huggingface.co/datasets/unlimitedbytes/hailuo-ai-voices.dia-aishell4-test
AISHELL-4 — test split (meeting diarization)
Copie du split test d'AISHELL-4, un corpus de réunions en mandarin capturé
par un array de 8 micros (on garde ici la version single-channel extraite
pour les benchmarks diarisation).
Contenu
20 sessions de réunion (3–7 speakers / session, durée variable)
Audio : FLAC mono
Annotations : RTTM par session
Langue : mandarin (zh)
Licence : Apache-2.0 (upstream)
Structure
dia-aishell4-test/
├── audio/test/<file_id>.flac… See the full description on the dataset page: https://huggingface.co/datasets/ggfox00000/dia-aishell4-test.Nufo
Ewe ASR Benchmark
Name: Nuƒo
language: ee
license: cc-by-4.0
task_categories:
automatic-speech-recognition
tags:
automatic-speech-recognition
asr
speech
ewe
low-resource
african-languages
configs:
config_name: waxal
data_dir: waxal
default: true
config_name: waxal_bibletts
data_dir: waxal_bibletts
config_name: waxal_bibletts_mina
data_dir: waxal_bibletts_mina
Nuƒo
A consolidated benchmark dataset for Automatic Speech Recognition… See the full description on the dataset page: https://huggingface.co/datasets/medbridge-ai/Nufo.thai-dialect-isan-dataset
Dataset Card for Thai Dialect Isan Speech Corpus
Dataset Description
This dataset contains audio recordings of Isan (Northeastern Thai) speech, paired with rich transcriptions and demographic metadata. It is designed to support Automatic Speech Recognition (ASR), dialect study, and text normalization tasks for the Isan language.
The dataset features spontaneous responses to specific questions, covering two domains (General and Finance), recorded by speakers from different… See the full description on the dataset page: https://huggingface.co/datasets/typhoon-ai/thai-dialect-isan-dataset.Meta_STT_ZH_AIShell3
Meta Speech Recognition Mandarin Dataset (AISHELL3)
This dataset contains both metadata and audio files for Mandarin speech recognition samples from the AISHELL3 corpus.
Dataset Statistics
Splits and Sample Counts
train: 60098 samples
valid: 3163 samples
test: 24772 samples
Example Samples
train
{
"audio_filepath": "/external4/datasets/Mandarin/AISHELL3/wavs_train/SSB00430356.wav",
"text": "她以 ENTITY_PRODUCT 滴鸡精 END 调养身体。 AGE_14_25… See the full description on the dataset page: https://huggingface.co/datasets/WhissleAI/Meta_STT_ZH_AIShell3.parlament_parla_v3
Dataset Card for ParlamentParla v3 - Speech Corpus of Catalan Parliamentary Sessions
A speech corpus composed of Catalan Parliamentary Sessions.The v3 and last version of the corpus includes both clean and other quality segments, divided into short segments (less than 30 seconds) and long segments (more than 30 seconds). The total dataset encompasses 1059h 48m 04s of speech, including 945h 51m 06s for the short segments and 113h 56m 58s for the long segments, with a total of… See the full description on the dataset page: https://huggingface.co/datasets/projecte-aina/parlament_parla_v3.knesset-plenums-whisper-training
Dataset Card for ivrit.ai - Knesset Plenums Whisper Training
This is a whisper-formatted version of the ivrit.ai Knesset Plenums dataset.
This dataset was created by splitting long audio recordings, along with their respective transcriptions, into audio slices of 30 seconds or less.
Each such slice represents one or more consecutive segments, along with timestamp token data and the previous slice's transcription.
The code for this dataset preparation process is available on the… See the full description on the dataset page: https://huggingface.co/datasets/ivrit-ai/knesset-plenums-whisper-training.dutch-tts-labeled-complete
Dutch TTS Dataset - Complete Labeled
A comprehensive Dutch text-to-speech dataset with 596,508 audio samples totaling 234GB of audio data.
Quick Preview
The default config shows a 100-row sample for the dataset viewer. To access the full dataset, use the full config.
Dataset Description
This dataset contains Dutch speech recordings with rich metadata including:
Emotion labels (neutral, happy, sad, angry)
Speaker IDs (239,388 unique speakers)… See the full description on the dataset page: https://huggingface.co/datasets/AITRADER/dutch-tts-labeled-complete.a5sv2-asr-benchmark-dataset
A5Sv2 ASR Benchmark Dataset
Public references, saved predictions, scores, and provenance for the
A5Sv2 ASR benchmark. The benchmark evaluates
streaming English ASR on four fixed public corpora with approximately equal normalized reference
word counts.
Corpus
Fixed selection
Reference words
Audio in this repository
Mega-ASR / Voices-in-the-Wild-2M
1,250 utterances, 250 per acoustic condition
32,928
Yes
AMI
7 scenario-only unseen-evaluation meetings
32,928
Yes
DiPCo… See the full description on the dataset page: https://huggingface.co/datasets/AirCaps/a5sv2-asr-benchmark-dataset.VoiceIsolation-Benchmark-Dataset
Voice Isolation Benchmark Dataset
265 real-world recordings for measuring how a second voice breaks speech-to-text, and how much Krisp Voice Isolation fixes it. Three scenarios, 47 speakers, real rooms, real headsets. No synthetic mixing.
265 recordings · 47 speakers · 3 scenarios · 65 scripts
Why this dataset exists
Modern STT engines handle noise well. They still fail when a second person talks near the microphone: they transcribe the wrong speaker, and voice… See the full description on the dataset page: https://huggingface.co/datasets/Krisp-AI/VoiceIsolation-Benchmark-Dataset.genshin-voice-v3.4-mandarin
Dataset Card for Genshin Voice
Dataset Description
Dataset Summary
The Genshin Voice dataset is a text-to-voice dataset of different Genshin Impact characters unpacked from the game.
Languages
The text in the dataset is in Mandarin.
Dataset Creation
Source Data
Initial Data Collection and Normalization
The data was obtained by unpacking the Genshin Impact game.
Who are the source language producers?
The… See the full description on the dataset page: https://huggingface.co/datasets/hanamizuki-ai/genshin-voice-v3.4-mandarin.thai-contextasr-bench
Thai Contextual-Biasing ASR Benchmark
TL;DR
Does your Thai ASR system actually use the context you give it (e.g., a list of names, custom words from your own dictionary) — and does it hallucinate when the context is irrelevant?
Each utterance comes with a bias list: entity strings (brands, person names,
places) that may or may not be spoken in the audio, written the way a real Thai user
would write them — one list, mixed Thai and Latin script. A good system does… See the full description on the dataset page: https://huggingface.co/datasets/wayu-ai/thai-contextasr-bench.bangla-10k
Bangla-10K: A Challenging, Metadata-Rich Corpus of Read and Conversational Bengali Speech from India and Bangladesh
Bangla-10K is a 10,816-hour Bengali speech corpus with
624,951 recordings from India and Bangladesh: a 10,070.8-hour core corpus
(567,323 recordings) and a separately collected 745.1-hour evaluation set
(57,628 recordings). It combines scripted single-speaker read speech with
natural multi-speaker conversations for Bengali automatic speech recognition
(ASR).
The… See the full description on the dataset page: https://huggingface.co/datasets/psdn-ai/bangla-10k.vietspeech500G of vietnamese speech corpus from Youtube
IndicCMix
IndicCMix
Most Indic NLP data assumes people write in one script and one language at a time. Real chat looks nothing like that. You get Hindi words in Roman letters, English verbs in the middle of a Tamil sentence, and the same person switching scripts halfway through a paragraph.
This dataset is an attempt to cover that actual messiness. For every English sentence, you get three different Indic renderings of it: one code-mixed in the native script, one clean native-script… See the full description on the dataset page: https://huggingface.co/datasets/ai4bharat/IndicCMix.hailuo-ai-jokes
Hailuo AI Jokes Dataset 🎤
A curated collection of high-quality voice recordings with corresponding transcriptions and phoneme analysis. This dataset is designed for speech recognition, text-to-speech, and voice analysis tasks.
🎙️ Dataset Content
The dataset contains a diverse set of synthetic voice recordings generated by Hailuo AI Audio. The texts are sourced from a variety of public domain jokes and humorous anecdotes. Each audio sample is accompanied by the… See the full description on the dataset page: https://huggingface.co/datasets/unlimitedbytes/hailuo-ai-jokes.Rural_Women_Bhojpuri
Rural Bhojpuri ASR Dataset
Dataset Description
This dataset is curated to foster the development of inclusive Automatic Speech Recognition (ASR) systems, with a special focus on the underrepresented voices of rural Bhojpuri women. It contains audio clips in both Bhojpuri and Hindi, collected from real-world and synthetic sources, designed to train and evaluate ASR models that can accurately recognize diverse speech patterns.
This work is part of the research presented in… See the full description on the dataset page: https://huggingface.co/datasets/ai4bharat/Rural_Women_Bhojpuri.maleo-short-1.5H
Dataset Card for Maleo Short 1.5H
Dataset Description
Dataset Summary
Maleo Short 1.5H is a manually curated, rigorously annotated speaker diarization dataset designed to benchmark State-of-the-Art (SOTA) models against complex, "in-the-wild" media domains. While modern diarization pipelines excel in controlled acoustic environments (like telephony or reading corpora), they heavily struggle with the overlapping speech, sound effects, and rapid speaker shifts… See the full description on the dataset page: https://huggingface.co/datasets/maleo-ai/maleo-short-1.5H.