Published June 19, 2026 | Version 1.0.0
Dataset Open

Earnings25: A Comprehensive 500-Hour Speech Benchmark for Finance

Description

Earnings25 is a large-scale benchmark for evaluating automatic speech recognition (ASR) systems on earnings-call audio in the financial domain.

The dataset comprises two complementary test sets:

• testset-full: 498 hours of full earnings calls from S&P 500 companies (2025 Q4), preserving full conversational structure.
• testset-segmented: 46 hours of industry-balanced 5–10 minute segments (290 industry classifications), sampled via stratified sampling from over 2,000 U.S. earnings calls (2025 Q1–Q4).

Earnings25 includes aligned transcripts, with timestamps obtained via CTC-based forced alignment, and rich structured metadata including:

  • speaker names and roles (operator, executive, analyst)

  • industry classification

  • company identifiers

The benchmark supports fine-grained ASR evaluation including speaker-aware and industry-aware analysis.

This dataset accompanies the Interspeech 2026 dataset-track submission:
“Earnings25: A Comprehensive 500-Hour Speech Benchmark for Finance”.

Files

earnings25.zip

Files (12.0 GB)

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