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

arXiv: https://arxiv.org/abs/2406.15668 · HTML: https://mlsanity.com/paper/2406.15668/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Jun 2024.

## Built on by (most cited first, 2 of 2)

- [NVCiM-PT: An NVCiM-assisted Prompt Tuning Framework for Edge LLMs](https://mlsanity.com/paper/2411.08244/) (2024)
- [Understanding Personalization Gains in Whisper](https://mlsanity.com/paper/2610.17019/) (2026)

## Abstract (arXiv)

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.