Automatic quantitative analysis of spontaneous aphasic speech

We describe our acoustic modeling method that sets a new recognition benchmark on AphasiaBank, a large-scale aphasic speech corpus. We propose a set of clinically-relevant quantitative measures that are shown to be highly robust to automatic transcription errors. Finally, we demonstrate that these measures can be used to accurately predict the revised Western Aphasia Battery (WAB-R) Aphasia Quotient (AQ) without the need for manual transcripts. The results and techniques presented in our work will help advance the state-of-the-art in aphasic speech processing and make ASR-based technology for aphasia treatment more feasible in real-world clinical applications.
Source: Speech Communication - Category: Speech-Language Pathology Source Type: research