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.earnings25
Earnings25
A 500-hour speech benchmark for finance — S&P 500 earnings calls with reference
transcripts, industry labels, and named-speaker attribution.
Citation
Earnings25 is introduced in our Interspeech 2026 paper,
which sets out the sampling design, the evaluation protocol, and reference
baselines for Whisper and Parakeet-TDT. Start there for the full picture.
Jiang, D., Zhou, H., Wadhawan, A., Fahy, B., Ramesh, V., Weisberg, D.,
Derkachevskiy, D., Sheehan, H., Prasad, S., &… See the full description on the dataset page: https://huggingface.co/datasets/florencejiang/earnings25.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.EarningsCallVoice
EarningsCallVoice: Core-100
EarningsCallVoice is a benchmark family for studying executive vocal delivery
in earnings-call question answering. Core-100 contains 100 manually
verified units. Each unit provides:
an authentic reference clip from the executive's prepared remarks;
the text of an analyst question;
an authentic answer clip from the same executive in the Q&A;
exact reference and answer transcripts;
cryptographic hashes and technical metadata.
The question is text… See the full description on the dataset page: https://huggingface.co/datasets/gmarti/EarningsCallVoice.earnings22-long-form