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arXiv · 2406.15668

PI-Whisper: Designing an Adaptive and Incremental Automatic Speech Recognition System for Edge Devices

Amir Nassereldine·Dancheng Liu·Chenhui Xu·Ruiyang Qin·Yiyu Shi·Jinjun Xiong
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Abstract

Edge-based automatic speech recognition (ASR) technologies are increasingly prevalent in the development of intelligent and personalized assistants. However, resource-constrained ASR models face significant challenges in adaptivity, incrementality, and inclusivity when faced with a diverse population. To tackle those challenges, we propose PI-Whisper, a novel ASR system that adaptively enhances recognition capabilities by identifying speakers' characteristics in real-time. In this work, we show how the design of PI-Whisper allows for incremental adaptation of new characteristics without the need for repetitive retraining, enhances recognition capabilities, and improves equity and fairness across diverse speaker groups. PI-Whisper demonstrates these advantages by achieving state-of-the-art accuracy, reducing the word error rate (WER) by up to 13.7% relative to baselines while scaling linearly to computing resources.

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Amir Nassereldine, Dancheng Liu, Chenhui Xu, Ruiyang Qin, Yiyu Shi, Jinjun Xiong. 2024-12-23. PI-Whisper: Designing an Adaptive and Incremental Automatic Speech Recognition System for Edge Devices. https://arxiv.org/abs/2406.15668

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