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.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.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.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.bharatvani-hindi-showcase
BharatVani Hindi Speech Corpus • Public Interactive Showcase
150-Hour Enterprise Devanagari Hindi Speech Corpus & Precomputed Latents
Curated & Mastered by BharatVani AI • TheCreatorOS
1. Interactive Dataset Preview
This repository is the official public evaluation showcase for the 150-Hour BharatVani Hindi Speech Corpus (103,784 Studio Clips).
Use the Dataset Viewer above to play real audio clips, inspect the word-level timestamp alignments, and… See the full description on the dataset page: https://huggingface.co/datasets/Sheeba2026/bharatvani-hindi-showcase.EGYSpeak
EGYSpeak
A curated dataset of 147,979 single-speaker Egyptian Arabic (pure dialect) audio clips with transcriptions, sourced from the fadisarwat/egyptian-arabic-lines Kaggle dataset and processed through a rigorous ASR pipeline.
Quick Start
1. Download the dataset:
from huggingface_hub import snapshot_download
snapshot_download(
repo_id="MohamedGomaa30/EGYSpeak",
repo_type="dataset",
local_dir="EGYSpeak",
)
2. Extract the dataset:
from… See the full description on the dataset page: https://huggingface.co/datasets/mahir2111/EGYSpeak.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.deafbench-synthetic-v2
DeafBench synthetic-v2
DeafBench synthetic-v2 is a frozen, 25-sample benchmark specification for
testing whether automatic speech recognition systems preserve information that
matters in accessible captions. It keeps conventional word error rate separate
from typed critical-information recall so a plausible transcript cannot hide a
lost time, digit sequence, username, code, Wi-Fi name, or proper name.
This repository publishes the reference text and reproducibility metadata. It… See the full description on the dataset page: https://huggingface.co/datasets/kvjones0243/deafbench-synthetic-v2.