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On the Interpretability of Whisper Encodings Using Sparse Autoencoders
arXiv cs.CL — Computation and Language
Factual evidence
What the source reports
Research explored the internal representations of OpenAI's Whisper encoder using sparse autoencoders, finding diverse linguistic and non-linguistic features.
OneBench interpretation
Institutional assessment
So what
Advancements in ASR model interpretability directly support your model risk and explainability requirements for deploying speech-based AI in critical banking functions.
Do what
This research provides a pathway for evaluating the explainability of ASR models like Whisper, which is crucial for their potential use in compliance or customer interaction analysis.