
Hugging Face Blog
· 1 min read
Adding Benchmaxxer Repellant to the Open ASR Leaderboard
"When a measure becomes a target, it ceases to be a good measure." (Goodhart’s Law)
TLDR: Appen Inc. and DataoceanAI have provided high-quality English ASR datasets covering scripted and conversational speech over multiple accents. To prevent potential risks of benchmaxxing or test-set contamination, we will keep these datasets private for a high-quality measure of performance on multiple tasks.
We’re not updating the average WER at this time: by default, the leaderboard’s Average WER remains computed on public datasets only. You can optionally include the private datasets using the toggle to see their impact 👀
Since its launch in September 2023, the Open ASR Leaderboard has been visited over 710K times. We’re blown away by the community’s interest and motivation to keep pushing speech recognition 🗣️
Two words sum up the objectives (but also challenges) in maintaining a benchmark like the Open ASR Leaderboard:
Standardization: models can have different conventions for their usage and outputs, e.g. with/without punctuation and casing. Datasets have the same challenges and can be structured differently. To this end, all test sets have been gathered into a single dataset on the Hub for easy access and previewing. Moreover, to standardize model outputs and dataset transcripts, we use a normalizer that (among other things) removes punctuation and casing, and maps to American spelling. It is based on the normalizer of Whisper.
Openness: the UI code and evaluation scripts are open-sourced. This has helped not only to incorporate new models, but also to improve the quality of the evaluation procedure through community feedback and contributions.
New high-quality, private datasets
To this end, we have worked with Appen Inc. and DataoceanAI to curate high-quality datasets for ASR benchmarking. Below is some information on the various splits.
Below are sample audio showing the variety of content (scripted, conversational, acronyms, disfluencies, proper nouns).
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