Title :
A dialogue system for accessing drug reviews
Author :
Liu, Jingjing ; Seneff, Stephanie
Author_Institution :
MIT Comput. Sci. & Artificial Intell. Lab., Cambridge, MA, USA
Abstract :
In this paper, we present a framework which harvests grassroots-generated data from the Web (e.g., reviews, blogs), extracts latent information from these data, and provides a multimodal interface for review browsing and inquiring. A prescription-drug domain system is implemented under this framework. Patient-provided drug reviews were collected from various health-related forums, from which significant side effects correlated to each drug type were identified with association algorithms. A multimodal web-based spoken dialogue system was implemented to allow users to inquire about drugs and correlated side effects as well as browsing the reviews obtained from the Web. We report evaluation results on speech recognition, parse coverage and system response.
Keywords :
Internet; Web sites; drugs; medical information systems; speech-based user interfaces; World Wide Web; association algorithm; blogs; correlated side effect; dialogue system; grassroots-generated data; health-related forum; inquiring; multimodal Web-based spoken dialogue; multimodal interface; parse coverage; patient-provided drug review; prescription-drug domain system; review browsing; speech recognition; system response; Antidepressants; Databases; Grammar; Muscles; Pain; Speech recognition;
Conference_Titel :
Automatic Speech Recognition and Understanding (ASRU), 2011 IEEE Workshop on
Conference_Location :
Waikoloa, HI
Print_ISBN :
978-1-4673-0365-1
Electronic_ISBN :
978-1-4673-0366-8
DOI :
10.1109/ASRU.2011.6163952
