Multilingual Aphasia Speech Analysis with Machine Learning


  • Rong Tong Singapore Institute of Technology
  • Shih-Cheng Yen National University of Singapore
  • Arthur Tay National University of Singapore
  • Yiting Emily Guo Singapore Institute of Technology, National University Hospital Singapore



Aphasia, Machine Learning, Speech Therapy, Language Analysis, Acoustic Analysis, Speech Classification


Aphasia is an acquired language disorder that occurs after brain injury such as stroke, head trauma or tumor. People with aphasia (PWA) may have trouble speaking or under-standing speech. If diagnosed early, aphasia is often treatable, and communication can be improved with speech therapy. Early detection and evaluation of aphasia is crucial for the treatment and recovery. This paper reports a preliminary study of multilingual aphasia speech evaluation. In this study, the characteristics of speech from PWA and healthy controls are compared from both acoustic and linguistic perspectives. Multiple acoustic features are extracted from aphasic and normal speech to build a language independent aphasic speech detection model. The model achieved good aphasic speech detection performance on both English and Mandarin test sets.