Automatic Early Detection of Amyotrophic Lateral Sclerosis from Intelligible Speech Using Convolutional Neural Networks
Kwanghoon An, Myungjong Kim, Kristin Teplansky, Jordan Green, Thomas Campbell, Yana Yunusova, Daragh Heitzman and Jun Wang
Abstract:
Amyotrophic lateral sclerosis (ALS) is a rapidly progressive neurodegenerative disease of the motor system that leads to the impairment of speech and swallowing functions. The lack of a biomarker typically causes a diagnostic delay. To advance the current diagnostic process, we explored the feasibility of automatic detection of patients with ALS at an early stage from highly intelligible speech. A speech dataset was collected from thirteen newly diagnosed patients with ALS and thirteen age- and gender-matched healthy controls. Convolutional Neural Networks (CNNs), including time-domain CNN and frequency-domain CNN, were used to classify the intelligible speech produced by patients with ALS and those by healthy individuals. Experimental results indicated both time- and frequency-CNN outperformed standard neural network. The best sample-level sensitivity and specificity were obtained by time-CNN (71.6% and 80.9%, respectively). When multiple samples were used to vote to estimate a person-level performance, the best result was obtained by frequency-CNN (76.9% sensitivity and 92.3% specificity). Results demonstrated the possibility of early detection of ALS from intelligible speech signals.
Cite as: An, K., Kim, M., Teplansky, K., Green, J., Campbell, T., Yunusova, Y., Heitzman, D., Wang, J. (2018) Automatic Early Detection of Amyotrophic Lateral Sclerosis from Intelligible Speech Using Convolutional Neural Networks. Proc. Interspeech 2018, 1913-1917, DOI: 10.21437/Interspeech.2018-2496.
BiBTeX Entry:
@inproceedings{An2018,
author={Kwanghoon An and Myungjong Kim and Kristin Teplansky and Jordan Green and Thomas Campbell and Yana Yunusova and Daragh Heitzman and Jun Wang},
title={Automatic Early Detection of Amyotrophic Lateral Sclerosis from Intelligible Speech Using Convolutional Neural Networks},
year=2018,
booktitle={Proc. Interspeech 2018},
pages={1913--1917},
doi={10.21437/Interspeech.2018-2496},
url={http://dx.doi.org/10.21437/Interspeech.2018-2496} }