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eess.AS2025
Towards a Single ASR Model That Generalizes to Disordered Speech
Jimmy Tobin, Katrin Tomanek, Subhashini Venugopalan
This study investigates the impact of integrating a dataset of disordered speech recordings (1,000 hours) into the fine-tuning of a near state-of-the-art ASR baseline system.…
eess.AS2024
Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning
Chirag Nagpal, Subhashini Venugopalan, Jimmy Tobin +3
We introduce a large language model (LLM) capable of processing speech inputs and show that tuning it further with reinforcement learning on human preference (RLHF) enables it to a…
eess.AS2024
Learnings from curating a trustworthy, well-annotated, and useful dataset of disordered English speech
Pan-Pan Jiang, Jimmy Tobin, Katrin Tomanek +6
Project Euphonia, a Google initiative, is dedicated to improving automatic speech recognition (ASR) of disordered speech. A central objective of the project is to create a large, h…