Earnings25: A Comprehensive 500-Hour Speech Benchmark for Finance
We introduce Earnings25, a finance-domain benchmark for evaluating automatic speech recognition (ASR) on English-language earnings calls under realistic conditions. Earnings25 comprises two complementary test sets: (i) testset-full, 498 hours of full English-language S&P 500 earnings calls from Q4 2025, and (ii) testset-segmented, a 46-hour industry-balanced set of 290 segments sampled from English-language U.S. earnings calls in 2025. The benchmark provides aligned transcripts and structured metadata, including speaker roles, industry labels, and call structure, enabling speaker- and industry-aware evaluation beyond aggregate word error rate (WER). We report reproducible baselines for Wh...
| Authors | Denglin Jiang, Haoran Zhou, Anshul Wadhawan et al. |
|---|---|
| Primary category | cs.CL |
| Published | 26 July 2026 |
| Last updated at source | 26 July 2026 |
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