datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Earnings22-Cleaned-AA
Earnings22-Cleaned-AA
Quick links: AA Speech-to-Text Leaderboard | AA-WER v2.0 article
Earnings22-Cleaned-AA is a cleaned subset of the English Earnings-22 test data from esb/datasets, a corpus of corporate earnings calls from global companies with speakers of many different nationalities and accents. This cleaned subset is the Earnings-22 portion included in AA-WER v2. We manually reviewed and corrected errors in the original ground-truth transcriptions to ensure fairer evaluation… See the full description on the dataset page: https://huggingface.co/datasets/ArtificialAnalysis/Earnings22-Cleaned-AA.LEMAS-Dataset-train
Overview
This dataset is part of LEMAS-Project (lemas-project.github.io/LEMAS-Project).
It contains a large-scale training set (150k+ hours) and a curated evaluation set
(500 utterances per language) covering 10 languages, all with word-level alignment.
Fields
key: unique utterance identifier; the first two characters indicate the language ID
audio: relative path to the MP3 audio file (in the eval set, this key is renamed to "file_name" for compatibility with the viewer)… See the full description on the dataset page: https://huggingface.co/datasets/LEMAS-Project/LEMAS-Dataset-train.Granary
Granary: Speech Recognition and Translation Dataset in 25 European Languages
Granary is a large-scale, open-source multilingual speech dataset covering 25 European languages for Automatic Speech Recognition (ASR) and Automatic Speech Translation (AST) tasks.
Overview
Granary addresses the scarcity of high-quality speech data for low-resource languages by consolidating multiple datasets under a unified framework:
🗣️ ~1M hours of… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Granary.spanish-slang-stt-data
Spanish Regional Speech-to-Text Dataset
A multilingual Spanish speech recognition dataset covering 4 regional dialects for fine-tuning Whisper and other ASR models.
Dataset Description
This dataset contains ~39,000 audio samples with transcriptions across 4 Spanish-speaking regions:
Region
Samples
Description
Mexico
17,725
Mexican Spanish including CIEMPIESS corpus
Spain
11,360
Castilian Spanish from TEDx and Common Voice
Argentina
5,839
Rioplatense Spanish… See the full description on the dataset page: https://huggingface.co/datasets/shraavb/spanish-slang-stt-data.apptek_callcenter_dialogues
AppTek Call-Center Dialogues: A Multi-Accent Long-Form Benchmark for English ASR
AppTek Call-Center Dialogues is a long-form conversational speech dataset for automatic speech recognition (ASR), featuring diverse English accents
across multiple service-oriented domains and designed to evaluate models on realistic call-center interactions.
128.6 hours of speech
14 English accent groups
16 service domains
5–15 minute conversations (long-form)
Split-channel audio (one… See the full description on the dataset page: https://huggingface.co/datasets/apptek-com/apptek_callcenter_dialogues.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.StreamAudio-2M
StreamAudio-2M
Large-scale streaming-audio dataset for audio-LLM / audio-agent training. Each row is a
stream: a sequence of audio turns sharing one unified schema. ~2.28M unique audio clips
are organised into six task subsets.
Subsets
Subset
Rows
Description
Stream_Audio_Understanding
90,738
Montages of audio-understanding clips (AudioSet / FMA): captions, choice & open QA
Real_time_ASR
28,109
Streams of ASR clips (CommonVoice / GigaSpeech /… See the full description on the dataset page: https://huggingface.co/datasets/zhifeixie/StreamAudio-2M.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.ContextASR-Bench
ContextASR-Bench: A Massive Contextual Speech Recognition Benchmark
Automatic Speech Recognition (ASR) has been extensively investigated, yet prior benchmarks have largely focused on assessing the acoustic robustness of ASR models, leaving evaluations of their linguistic capabilities relatively underexplored. This largely stems from the limited parameter sizes and training corpora of conventional ASR models, leaving them with insufficient world knowledge, which is crucial for… See the full description on the dataset page: https://huggingface.co/datasets/MrSupW/ContextASR-Bench.UltraVoice
UltraVoice: Scaling Fine-Grained Style-Controlled Speech Conversations for Spoken Dialogue Models
📝 Abstract
Spoken dialogue models currently lack the ability for fine-grained speech style control, a critical capability for human-like interaction that is often overlooked in favor of purely functional capabilities like reasoning and question answering. To address this limitation, we introduce UltraVoice, the first large-scale speech dialogue dataset… See the full description on the dataset page: https://huggingface.co/datasets/tutu0604/UltraVoice.Earnings22-Cleaned-AA-chunked
Earnings22-Cleaned-AA-chunked
Quick links: AA Streaming Speech to Text Leaderboard | Speech to Text methodology
Earnings22-Cleaned-AA-chunked is a chunked version of Earnings22-Cleaned-AA, the cleaned Earnings-22 subset used by Artificial Analysis for streaming Speech to Text evaluation.
The original Earnings-22 data comes from esb/datasets, a corpus of corporate earnings calls. Artificial Analysis manually reviewed and corrected the reference transcripts in the cleaned subset… See the full description on the dataset page: https://huggingface.co/datasets/ArtificialAnalysis/Earnings22-Cleaned-AA-chunked.HearInContextEnglish | 中文
HearInContext
A Benchmark for Implicit Context in Speech Recognition
Illustrative example: the same spoken request is disambiguated as flour or flower by different assistant histories. The dialogue and waveform are illustrative.
Same audio. Different contexts. Different meanings.
HearInContext is a Mandarin–English contextual speech recognition benchmark. It pairs the same audio with dialogue histories supporting different meanings to evaluate… See the full description on the dataset page: https://huggingface.co/datasets/OPPOer/HearInContext.VoxPopuli-Cleaned-AA
VoxPopuli-Cleaned-AA
Quick links: AA Speech to Text Leaderboard | AA-WER v2.0 article
VoxPopuli-Cleaned-AA is a cleaned subset of the English VoxPopuli test data from esb/datasets, a speech dataset derived from European Parliament recordings. This cleaned subset is the VoxPopuli portion included in AA-WER v2. We manually reviewed and corrected errors in the original ground-truth transcriptions to ensure fairer evaluation of Speech to Text (STT) models.
This dataset is part of AA-WER… See the full description on the dataset page: https://huggingface.co/datasets/ArtificialAnalysis/VoxPopuli-Cleaned-AA.garhwali-corpus
Garhwali Language Lab
Current developer status — 8 October 2026
The live Dataset Viewer reports 20 configurations, 31 config/split views, and
963,484 displayed rows. These views overlap and include source indexes; they
are not 963,484 distinct training examples. The screened_meta_gbm view has
1,841 automatically screened sentence-length transcripts for exploratory
text training, and short_utterances_meta_gbm has 110 context rows. Both
reuse transcript values… See the full description on the dataset page: https://huggingface.co/datasets/rushilrawat/garhwali-corpus.bharatvani-hindi-speech-corpus
BharatVani Hindi Speech Corpus (205-Hour Studio Dataset)
Proprietary Speech Asset • TheCreatorOS • BharatVani AI
1. Overview
The BharatVani Hindi Speech Corpus is an enterprise-grade, high-fidelity Indian speech dataset engineered for speech foundation models, acoustic research, and voice synthesis in Devanagari Hindi & Conversational Hinglish.
Audio Clips: 99,475 Pristine, 1:1 Verified Audio Clips (24,000 Hz, 16-bit Mono PCM WAV)
Duration: ~205.3… See the full description on the dataset page: https://huggingface.co/datasets/Sheeba2026/bharatvani-hindi-speech-corpus.quran-tajweed-phonetics
The complete phonetic layer of the Quran in the riwaya of Hafs 'an
'Asim via tariq al-Shatibiyyah: 6,236 ayat, 522,475 phones, every
phone carrying its tajweed attribution: madd class with its transmitted
length range, ghunna grade, qalqalah class, tafkheem with its rank, sakt,
the seventeen sifat, and the rule that produced it.
Built and maintained by Quran Lab, a waqf building open technology in
the service of the Quran.
How it was built and verified
Indexed from the… See the full description on the dataset page: https://huggingface.co/datasets/Quran-Lab/quran-tajweed-phonetics.cv-corpus-25.0-ja
Mozilla Common Voice 25.0 - Japanese Test Set (Complete)
Dataset Description
Complete Japanese test set from Mozilla Common Voice Corpus 25.0. This dataset contains all 9,019 validated test samples, compared to the partial 2,334-sample version previously available on HuggingFace.
Key Features
Size: 9,019 validated test utterances
Coverage: 100% of official Common Voice 25.0 Japanese test split
Multi-speaker: Diverse set of speakers with demographic metadata… See the full description on the dataset page: https://huggingface.co/datasets/FluidInference/cv-corpus-25.0-ja.darija-asr-corpus
Darija ASR Corpus (dataset-core)
Arabizi (Latin-script) transcriptions of Moroccan Darija speech, produced for a
Whisper fine-tuning pipeline (paper not yet published -- citation forthcoming).
This repo contains four source subsets: DODa, DVoice, Wiki, and
YouTube. Each subset carries its own upstream license/terms -- see below --
because they are drawn from four different original projects.
Subsets
Config
Rows
Audio bundled?
Upstream license
Upstream source… See the full description on the dataset page: https://huggingface.co/datasets/abnajlae/darija-asr-corpus.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.simsamu
Simsamu dataset
This repository contains recordings of simulated medical dispatch dialogs in the
french language, annotated for diarization and transcription. It is published
under the MIT license.
These dialogs were recorded as part of the training of emergency medicine
interns, which consisted in simulating a medical dispatch call where the interns
took turns playing the caller and the regulating doctor.
Each situation was decided randomly in advance, blind to who was playing the… See the full description on the dataset page: https://huggingface.co/datasets/medkit/simsamu.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.MM-ContextASR-Bench
MM-ContextASR Bench
Metadata and evaluation splits for Multimodal Conversational Context for
LLM-Based ASR: Data Construction, Training, and Benchmark.
Dataset summary
Config
Examples
Audio
Context
Primary metric
mm_contextasr
1,250 (250 current utterances × 5 histories)
1,439 WAV files included
Controlled user-assistant dialogue
entity Recall
kespeech
19,212
Source ID only
Same-speaker speech and transcript
CER, SER, entity Recall
cv_yue
3,525… See the full description on the dataset page: https://huggingface.co/datasets/lilonghao/MM-ContextASR-Bench.pavo-bench
PAVO-Bench: 50K-Turn Benchmark for ASR-LLM-TTS Pipeline Routing
Code: github.com/vnmoorthy/pavo-bench · Paper: TMLR 2026 (accepted) · Authors: NarasingaMoorthy VeiluKanthaPerumal (UPenn), Mohammed Imthathullah (Google)
pip install git+https://github.com/vnmoorthy/pavo-bench.git
Headline results (vs fixed-cloud baseline, 50,000 voice turns)
Metric
Result
Significance
P95 end-to-end latency (H100, LibriSpeech)
−10.3% (−167 ms)
—
Median latency
−34%… See the full description on the dataset page: https://huggingface.co/datasets/vnmoorthy/pavo-bench.teochew_wild
Teochew-Wild：首个正字标注的野外潮州话数据集
中文 | English
本数据集（Teochew-Wild）是从网络上发音清晰、噪声较少的音视频内容中获取的，原始音视频的数据来源为：民生新闻、潮汕讲古、地方电视节目、故事书、抖音自媒体口播等，我借鉴了Emilla提出的数据集自动处理流水线，对原始数据进行归一化、降噪和剪切（部分自动剪切效果差的使用手工修正）；
Teochew-Wild总共包括20个发音标准、念错率低的潮汕母语说话人、共12500条音频片段，包含潮州市区、汕头市区、澄海、榕江音、潮安南部等多个区域的口音，语料内容覆盖书面用语与口头用语，并同时提供正字和拼音标注，是首个公开可用、标注准确率高的潮州话数据集，主要面向语音识别和语音合成任务。
文件说明 （File Structure Explanation）
├── annotation/ # 标注相关文件夹
│ ├── label_for_qwen_asr/ #… See the full description on the dataset page: https://huggingface.co/datasets/panlr/teochew_wild.multichannel-meetings-10h
GroundTruth Multi-Channel Meeting Audio Dataset (10h)
Summary
This dataset contains approximately 10 hours of co-located, multi-speaker meeting recordings, each captured simultaneously via a room (built-in) microphone and individual close-talk lapel microphones worn by each participant.
Each meeting includes:
One full meeting recording (room microphone)
Individual close-talk recordings for each participant (one file per speaker)
Structured metadata describing speakers… See the full description on the dataset page: https://huggingface.co/datasets/ground-truth/multichannel-meetings-10h.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.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/yunqi1766/voice-code-bench.quran-asr-husary
Quran ASR — Husary Muallim Dataset
Description
This dataset contains Quran recitation audio files by Sheikh Mahmoud Khalil Al-Husary at 16 kHz sampling rate, with Arabic transcriptions including diacritics.
Dataset Structure
Audio files: Stored in audio/ folder (e.g., audio/001_001.wav)
Data file: manifest.json (NeMo format)
Columns:
audio_filepath: Path to audio file
text: Arabic transcription with diacritics
duration: Audio duration in seconds
speaker:… See the full description on the dataset page: https://huggingface.co/datasets/NightPrince/quran-asr-husary.modelroom-catalog
Open Model Catalog
A small table of the models their publishers call current: text, vision, embedding, speech
recognition, image and video generation. Not every build on the Hub. One row per model, with the
publisher page that says it is current and the date that was checked.
247 models · 56 publisher accounts watched · one JSON file (183 KB) · schema 2 · CC BY 4.0
What a row carries
Field
Meaning
hf_repo, publisher, family, kind
the repository, its… See the full description on the dataset page: https://huggingface.co/datasets/jm-vis/modelroom-catalog.FTAR
TimeAudio: Bridging Temporal Gaps in Large Audio-Language Models
Abstract
Recent Large Audio-Language Models (LALMs) exhibit impressive capabilities in understanding audio content for conversational QA tasks. However, these models struggle to accurately understand timestamps for temporal localization (e.g., Temporal Audio Grounding) and are restricted to short audio perception, leading to constrained capabilities on fine-grained tasks. We identify three key aspects that limit… See the full description on the dataset page: https://huggingface.co/datasets/lysanderism/FTAR.