A dialogue system for accessing drug reviews

Author

Liu, Jingjing ; Seneff, Stephanie

Author_Institution

MIT Comput. Sci. & Artificial Intell. Lab., Cambridge, MA, USA

fYear

2011

fDate

11-15 Dec. 2011

Firstpage

324

Lastpage

329

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ASRU.2011.6163952

Filename

6163952