Pronunciation Robustness
Progress Over Time
Interactive timeline showing model performance evolution on Pronunciation Robustness
Pronunciation Robustness Leaderboard
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 | Fish Audio | 35B | — | — |
Sub-benchmarks
Pronunciation Robustness (Context)
Artificial Analysis Pronunciation Robustness subcategory: words whose reading depends on context.
Pronunciation Robustness (Exact Sequences)
Artificial Analysis Pronunciation Robustness subcategory: exact sequences such as codes, paths, and emails.
Pronunciation Robustness (Names)
Artificial Analysis Pronunciation Robustness subcategory: names of brands, places and technical terms.
Pronunciation Robustness (Shorthand)
Artificial Analysis Pronunciation Robustness subcategory: shorthand including numbers, dates, units, and notation.
What is Pronunciation Robustness?
Artificial Analysis Pronunciation Robustness evaluates how often text-to-speech models correctly read hard words in English sentences (numbers, codes, brand names, and words whose reading depends on context).
Pronunciation Robustness is a audio benchmark evaluating models on general and audio tasks. LLM Stats tracks 1 models on this benchmark, scored on a 0–1 scale. The current average is 0.9, with the leader at 0.9.
Compare leaders on the best AI for general and best AI for audio leaderboards.
Current leaders
Fish Audio Drama 3 from Fish Audio currently leads the Pronunciation Robustness leaderboard with a score of 0.932 across 1 evaluated AI models.
FAQ
Common questions about the Pronunciation Robustness benchmark and leaderboard.