Automatic speech recognition in neurodegenerative disease

Authors: Benjamin G. Schultz, Venkata S. Aditya Tarigoppula, Gustavo Noffs, Sandra Rojas, Anneke van der Walt, David B. Grayden, Adam P. Vogel; International Journal of Speech Technology, doi:10.1007/s10772-021-09836-w 

Automatic speech recognition (ASR) could potentially improve communication by providing transcriptions of speech in real time. ASR is particularly useful for people with progressive disorders that lead to reduced speech intelligibility or difficulties performing motor tasks. ASR services are usually trained on healthy speech and may not be optimized for impaired speech, creating a barrier for accessing augmented assistance devices. We tested the performance of three state-of-the-art ASR platforms on two groups of people with neurodegenerative disease and healthy controls. We further examined individual differences that may explain errors in ASR services within groups, such as age and sex. Speakers were recorded while reading a standard text. Speech was elicited from individuals with multiple sclerosis, Friedreich’s ataxia, and healthy controls. Recordings were manually transcribed and compared to ASR transcriptions using Amazon Web Services, Google Cloud, and IBM Watson.