SpeechEditBench - Emotion: leaderboard

Metric: Joint success (%): the requested edit is applied (task-specific automatic check) and the linguistic content is preserved (Whisper large-v3 or Paraformer transcript within 10% WER or CER of the expected text); source speech plus a natural-language instruction, English and Mandarin samples, each model through its released editing or conversation interface; emotion editing (convert to a target emotion, judged by a gemini-2.5-pro audio judge; half the items carry text whose affect conflicts with the target), 1400 samples; higher is better. Source: arxiv.org. Saturation forecast: Around 2030. 8 models tracked.

Top models

#ModelScore
1Qwen3 Omni 30B A3B Instruct1.64

Interactive version: theaggregate.ai/benchmark?slug=speecheditbench-emotion · How It Works · Data refreshed daily, snapshot 2026-09-29.