Chatphasia: a personalized end-to-end system for aphasia therapy
This paper introduces an AI-powered system designed to revolutionize therapy for aphasia patients by enhancing accessibility and personalization. The solution integrates a mobile application for patients to perform word-retrieval tasks and a web dashboard for practitioners to monitor progress and tailor therapy. Key components include a fine-tuned Automatic Speech Recognition (ASR) model optimized for Singaporean aphasic speech and a Large Language Model (LLM)-driven cue generation framework based on hierarchical techniques used in speech therapy. The combination of these components forges a comprehensive tool for speech rehabilitation, demonstrating significant improvements in usability, transcription accuracy, and therapy outcomes.
Authors
- Xin He (ORCID: https://orcid.org/0000-0002-5189-7204)
- Farhan Azmi
- Han Xiang Kee
- Ying Zhen Lee
- Wen Qin Yeo
- Tong Rong
Institutions
- Singapore Institute of Technology (SG)
Publication Details
- Published
- 2025-09-22
- DOI
- https://doi.org/10.1117/12.3077156
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 0.00