datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
WildElder
WILDELDER: A CHINESE ELDERLY SPEECH DATASET FROM THE WILD WITH FINE-GRAINED MANUAL ANNOTATIONS
Paper: https://huggingface.co/papers/2510.09344Code: https://github.com/NKU-HLT/WildElder
WildElder is a speech dataset focused on elderly scenarios. It contains raw audio and corresponding text annotations and can be used for ASR, speaker-related tasks, and front-/back-end speech processing research. The data was collected and cleaned from real-world environments to preserve diversity and… See the full description on the dataset page: https://huggingface.co/datasets/Hui519/WildElder.AudioMarathon
🎵 AudioMarathon: A Comprehensive Benchmark for Long-Context Audio Understanding and Efficient Inference in Multimodal LLMs
Abstract
AudioMarathon is a large-scale, multi-task audio understanding benchmark designed to systematically evaluate audio language models' capabilities in processing and comprehending long-form audio content. It provides a diverse set of 10 tasks built upon three pillars:
long-context audio inputs with durations ranging from 90.0 to 300.0… See the full description on the dataset page: https://huggingface.co/datasets/Hezep/AudioMarathon.wikimedia-common-audio-catalanThis is a collection of Catalan-language audio with free licenses extracted from Wikimedia Commons.
License identifiers are normalized to cc-zero, cc-by-4.0,
cc-by-sa-3.0, cc-by-sa-4.0, GFDL, and PD-self.
This provides a richer alternative to Common Voice.
Characteristics of the dataset:
One or multiple speakers
Different accents
Different domain texts
761 audio files
We found this dataset useful for audio tasks such as:
Language detection
Evaluation of STT systems
New candidates are… See the full description on the dataset page: https://huggingface.co/datasets/softcatala/wikimedia-common-audio-catalan.Chinese-LiPS
Chinese-LiPS: A Chinese audio-visual speech recognition dataset with Lip-reading and Presentation Slides
⭐ Introduction
The Chinese-LiPS dataset is a multimodal dataset designed for audio-visual speech recognition (AVSR) in Mandarin Chinese. This dataset combines speech, video, and textual transcriptions to enhance automatic speech recognition (ASR) performance, especially in educational and instructional scenarios.
🚀 Dataset Details
Total Duration:… See the full description on the dataset page: https://huggingface.co/datasets/BAAI/Chinese-LiPS.parler-tts_mls_eng_10k_snac_token_old
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/blanchon/parler-tts_mls_eng_10k_snac_token_old.asr-jargon-specialized-vocabulary
A Dataset for Evaluating ASR on Specialized Vocabulary
Novel synthetic datasets from the paper "A Dataset for Evaluating ASR on Specialized Vocabulary" (LREC 2026).
Code and reproduction scripts: https://github.com/eduardogc8/ASR-Jargon-Dataset-Code
Configs
Config
Language
Description
synthetic_terms_en
English
Utterances embedding entirely novel, 100% OOV, LLM-generated technical terms
synthetic_terms_pt
Portuguese
Portuguese equivalent… See the full description on the dataset page: https://huggingface.co/datasets/egcortes/asr-jargon-specialized-vocabulary.AudioMarathon
AudioMarathon
AudioMarathon is a long-context audio benchmark for evaluating multimodal LLMs on speech, music, environmental audio, and meetings. The release package in this directory is organized around 11 benchmark tasks spanning meeting summarization, automatic speech recognition, reading comprehension, authenticity detection, music genre classification, acoustic scene classification, emotion recognition, spoken named entity reasoning, sound event detection, speaker gender… See the full description on the dataset page: https://huggingface.co/datasets/AudioMarathon/AudioMarathon.SynthGT
SynthGT
A Synthetic Solo-Singing Dataset for Singing-Oriented Forced Alignment
Authors
Silas Antonisen, Iván López-Espejo
Associated paper submitted to IEEE Transactions on Audio, Speech and Language Processing.
Overview
SynthGT (Synthetic Ground Truth) is a synthetic English solo-singing dataset containing 4,900 singing performances with automatically generated phoneme boundary annotations.
The dataset was created through music… See the full description on the dataset page: https://huggingface.co/datasets/Silasimo/SynthGT.Real-TurnTurk
Real-TurnTurk
English: Real-TurnTurk is a multimodal, two-channel Turkish dyadic conversation dataset built to improve turn-taking prediction in voice-based dialogue systems. Unlike Syn-TurnTurk, the other dataset we built, every conversation here is a real, unscripted exchange between two people, recorded over video calls. Each participant was captured on a separate audio channel, so speaker attribution is exact and requires no diarization model. Alongside the audio, the… See the full description on the dataset page: https://huggingface.co/datasets/tugrulbayrak/Real-TurnTurk.Neapolitan-Spoken-Corpus
Neapolitan Spoken Corpus (NSC)
A corpus of read Neapolitan speech for ASR evaluation, with a validated
Neapolitan–Italian lexicon, LOSO fine-tuning splits, trained LoRA adapters,
metric implementations, per-clip results, and error annotations.
This release supersedes the earlier 141-clip single-speaker version of this
repository. The earlier release corresponds to Speaker S1 of the present
corpus; the old audioData/ and transcripts.csv are replaced by
data/audio/ and… See the full description on the dataset page: https://huggingface.co/datasets/michaelcacioli/Neapolitan-Spoken-Corpus.knesset-plenums
About
This dataset is derived from raw a/v recordings and human-generated protocols of the Knesset (the Israeli house of representatives) plenums as part of the ivrit.ai project.
Consider visiting the preview space for this dataset here
Method
Data dumps from the Knesset contain A/V recordings, alongside proprietary protocols with timestamps.
We extract the audio stream, and clean up timestamp mistakes (such as backward jumps, or out-of-order timestamp artifacts).
The… See the full description on the dataset page: https://huggingface.co/datasets/ivrit-ai/knesset-plenums.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.barranquenho-ipa-dict-synthetic
Barranquenho IPA Pronunciation Dictionary
The first and only IPA pronunciation dictionary of Barranquenho — the
Ibero-Romance contact variety spoken in Barrancos (Baixo Alentejo, Portugal),
a mixed system born of centuries of Portuguese–Spanish (Extremaduran /
Andalusian) contact on the raia. Every headword is written in the
Convenção Ortográfica do Barranquenho (2025) orthography and paired with a
broad-phonemic IPA transcription plus Portuguese and Spanish glosses.
This… See the full description on the dataset page: https://huggingface.co/datasets/TigreGotico/barranquenho-ipa-dict-synthetic.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.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.VoiceCommandAudioThis is mainly used for fine tune "VoiceCommand" a speech congnition MOD dedicated for SilentHunter game series
Hadou-Voice-Dataset
Hadou Voice Dataset
ハドウ本人が収録した、日本語音声データセットです。
このページで、特徴の異なる2種類のデータセットを公開しています。
配布データ
設定名
内容
音声数
合計時間
v1（おすすめ）
Hadou Calm Voice Dataset v1。落ち着いた中音域、AIキャラクター向けボイスが多めの音声データ
966
約114.02分
v0
Hadou ITA Corpus Dataset v1。ITAコーパスを読み上げた自然な話し声
424
約38.95分
v1 には、AICAコーパス500文、ITAコーパス324文、感情・態度付き90文、同文異演技40文、強度段階12文を収録しています。
v1の詳細: v1/README.txt
v0の詳細: v0/README.txt
読み込み例
from datasets import load_dataset
# 新しい966音声（既定）
dataset =… See the full description on the dataset page: https://huggingface.co/datasets/hadou1225/Hadou-Voice-Dataset.script-fidelity-benchmark
Script fidelity benchmark
Anonymous supplement for the paper "Script collapse in multilingual ASR:
A reference-free metric and 100-pair benchmark."
Script Fidelity Rate (SFR) measures the fraction of ASR hypothesis characters
that belong to the expected target script. WER measures word edits, while SFR
checks whether the output is written in the target orthography.
Related resources:
PyPI package: https://pypi.org/project/script-fidelity/
Hugging Face Evaluate metric:… See the full description on the dataset page: https://huggingface.co/datasets/themechanism/script-fidelity-benchmark.central-kurdish-tts4all
TTS4All Central Kurdish Speech Dataset
Dataset Summary
The TTS4All Central Kurdish Speech Dataset is a multi-speaker speech corpus developed for speech synthesis and speech technology research in Central Kurdish (Sorani Kurdish).
The dataset was created within the TTS4All initiative during the JSALT 2025 Workshop and provides more than 35 hours of transcribed speech from three native Central Kurdish speakers.
The corpus was designed to support:
Text-to-Speech… See the full description on the dataset page: https://huggingface.co/datasets/aranemini/central-kurdish-tts4all.modicol
MoDiCoL - A Modular Diagnostic Continual Learning Dataset for ASR
MoDiCoL is a speech dataset designed to study the robustness of ASR models to different drift factors in a controlled, continual setting. We construct MoDiCoL using a systematic factorial design that enables a rigorous evaluation of linguistic, speaker, and acoustic variation with clearly defined experimental runs. By combining real-world and synthetic speech with a configuration-dependent augmentation pipeline… See the full description on the dataset page: https://huggingface.co/datasets/TPekarekRosin/modicol.WolBanking77Intent classification models have made a lot of progress in recent years. However, previous studies primarily focus on high-resource languages datasets, which results in a gap for low-resource languages and for regions with a high rate of illiterate people where languages are more spoken than read or written. This is the case in Senegal, for example, where Wolof is spoken by around 90% of the population, with an illiteracy rate of 42% for the country. Wolof is actually spoken by more than 10… See the full description on the dataset page: https://huggingface.co/datasets/karim155/WolBanking77.open-ko-s2s-eval-artifacts
Open Ko-S2S 평가 산출물 (감사용)
⚠️ KsponSpeech 참조 전사는 해시로 대체돼 있습니다
KsponSpeech 는 AI Hub 배포 데이터로 재배포 제한이 있을 수 있어, kspon 런의
ref 컬럼을 ref_sha256 으로 대체했습니다(전사 원문 미포함). 모델 출력(hyp)과
채점 결과(cer_err/cer_len/cer)는 우리 산출물이라 그대로 공개합니다.
Zeroth 런은 원본이 CC BY 4.0(OpenSLR #40)이라
ref 원문을 그대로 담고 있습니다.
라이선스 보유자의 검증 절차
AI Hub 에서 KsponSpeech 를 정당하게 받은 분은 다음으로 우리 수치를 검증할 수 있습니다.
리더보드 저장소의 eval/datasets_ko.py 에서 clean_kspon() 을 가져옵니다.
자기 사본의 원 전사에 clean_kspon() 을 적용합니다. 결과가 목록이면… See the full description on the dataset page: https://huggingface.co/datasets/baryonlabs/open-ko-s2s-eval-artifacts.clipquill-asr-benchmark
Measuring whisper-tiny vs whisper-base in a browser tab
Word error rate, wall-clock timing, transfer size and peak memory for two
quantised Whisper tiers running entirely client-side in a real Chrome window,
with the scripts that produced every number.
If you are building an in-browser transcription page, the two results worth
knowing before you pick a model tier:
On clean synthetic audio the two tiers tie. If that is all you test, you
will conclude the tier does not matter… See the full description on the dataset page: https://huggingface.co/datasets/sophia8888/clipquill-asr-benchmark.HALAS
Dataset Card for HALAS
Dataset Summary
HALAS (Hallucination Annotations for Large-scale ASR Systems) is a human-annotated dataset of hallucinations produced by modern automatic speech recognition (ASR) systems on real-world speech recordings. The dataset contains span-level hallucination annotations for ASR outputs generated from recordings in the Earnings22 corpus.
HALAS was introduced to address a key limitation in prior hallucination research: most existing… See the full description on the dataset page: https://huggingface.co/datasets/MatBar99/HALAS.uyghur-ASR-dataset
Uyghur ASR Corpus (Latin Transliteration)
A speech corpus for Uyghur automatic speech recognition, with transcriptions in a
case-sensitive Latin transliteration scheme. Approximately 23 hours of audio across
9,468 clips.
Uyghur is a Turkic language spoken by roughly 10–12 million people. It is severely
under-represented in open speech datasets, and this corpus is intended to support ASR research
for the language.
Dataset summary
Language
Uyghur (ug)… See the full description on the dataset page: https://huggingface.co/datasets/Shramadeepd/uyghur-ASR-dataset.sinhala-tts-dataset-archive-20260429-082457
Sinhala TTS Dataset
Clean, segmented Sinhala speech from the "Unlimited History" YouTube series by @sunchare.
Stats
Metric
Value
Utterances
218
Train
208
Val
10
Hours
0.51
Mean duration
8.5s
Sample rate
22050 Hz
Pipeline
Raw YouTube audio -> HTDemucs -> VoiceFixer + DeepFilterNet3 ->
Diarization -> Silero-VAD -> ASR (faster-whisper: C:\Users\kosal\sinhala-tts\whisper-small-si-ct2) -> Quality filtering (SNR>=20.0dB)
Format… See the full description on the dataset page: https://huggingface.co/datasets/outlawmold/sinhala-tts-dataset-archive-20260429-082457.ReadNet
ReadNet
Dataset Description
ReadNet is an audio dataset collected from more than 2,00,000 children in the age group of 5-16 years in Hindi and Marathi language.
The dataset consists of audio files in the wav format where children read out ASER Samples which consists of letters, words, stories and paragraphs in their native language.
This dataset is a subset of the larger dataset which consists of an estimated 2500 hours of data. This dataset consists of ~87 hours… See the full description on the dataset page: https://huggingface.co/datasets/PrathamOrgAI/ReadNet.slovenian-speech-recognition
Slovenian Speech Dataset
Dataset comprises 10+ hours of audio recordings featuring 20+ speakers engaged in telephone dialogues in the Slovenian language. It contains speech data designed for training robust language models and automatic speech recognition systems in real-world conversational scenarios.
By utilizing this dataset, researchers and developers can advance their understanding and capabilities in natural language processing (NLP), speech recognition, and machine… See the full description on the dataset page: https://huggingface.co/datasets/UniDataPro/slovenian-speech-recognition.id-en-codeswitch-dataset-alternative
Indonesian–English Code-Switching Synthetic Speech Dataset
Synthetic speech generated for the undergraduate final project "Handling
Code-Switching in Automatic Speech Recognition for Low-Resource Language
Pairs: An Indonesian–English Case Study", School of Electrical Engineering
and Informatics, Institut Teknologi Bandung.
This dataset contains synthetic audio produced from the Indonesian–English
code-switching text corpora released in the companion repository below. It
was used… See the full description on the dataset page: https://huggingface.co/datasets/shulhaaja/id-en-codeswitch-dataset-alternative.africanvoices-naija-batch1-summary
African Voices Naija Train Metadata Summary
This dataset contains a compact summary of metadata for the Naija training split, provided as CSV tables for inspection and analysis.
Files included:
batch_summary.csv
domain_distribution.csv
The repository contains metadata summaries only and does not include raw audio.