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Adapting Whisper for Lightweight and Efficient Automatic Speech Recognition of Children for On-device Edge Applications
Satwik Dutta, Shruthigna Chandupatla, John Hansen
https://arxiv.org/abs/2507.14451

Adapting Whisper for Lightweight and Efficient Automatic Speech Recognition of Children for On-device Edge Applications
Reliability on cloud providers for ASR inference to support child-centered voice-based applications is becoming challenging due to regulatory and privacy challenges. Motivated by a privacy-preserving design, this study aims to develop a lightweight & efficient Whisper ASR system capable of running on a Raspberry Pi. Upon evaluation of the MyST corpus and by examining various filtering strategies to fine-tune the `tiny.en' model, a Word Error Rate (WER) of 15.9% was achieved (11.8% filtered). A …