PI-Whisper: An Adaptive and Incremental ASR Framework for Diverse and Evolving Speaker Characteristics
<|reference_start|>PI-Whisper: An Adaptive and Incremental ASR Framework for Diverse and Evolving Speaker Characteristics: As edge-based automatic speech recognition (ASR) technologies become increasingly prevalent for the development of intelligent and personalized assistants, three important challenges must be addressed for these resource-constrained ASR models, i.e., adaptivity, incrementality, and inclusivity. We propose a novel ASR framework, PI-Whisper, in this work and show how it can improve an ASR's recognition capabilities adaptively by identifying different speakers' characteristics in real-time, how such an adaption can be performed incrementally without repetitive retraining, and how it can improve the equity and fairness for diverse speaker groups. More impressively, our proposed PI-Whisper framework attains all of these nice properties while still achieving state-of-the-art accuracy with up to 13.7% reduction of the word error rate (WER) with linear scalability with respect to computing resources.<|reference_end|>
@article{nassereldine2024pi-whisper:,
    title={PI-Whisper: An Adaptive and Incremental ASR Framework for Diverse and
  Evolving Speaker Characteristics},
    author={Amir Nassereldine, Dancheng Liu, Chenhui Xu, Jinjun Xiong},
    journal={arXiv preprint arXiv:2406.15668},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.15668},
    primaryClass={cs.CL cs.SD eess.AS}
}