DocumentCode
2967952
Title
COAST: Context-aware pervasive speech recognition system
Author
Aynehband, Meghdad ; Rahmani, Amir Masoud ; Setayeshi, Saeed
Author_Institution
Islamic Azad Univ., Dezful, Iran
fYear
2011
fDate
23-25 Feb. 2011
Firstpage
1
Lastpage
4
Abstract
Context-aware applications adapt their behavior to the user current situation. This paper presents a new architecture named COAST (Context-aware Speech to text translator). Reducing user interaction and selecting the best classifier based on contexts are the primary objectives in COAST and user´s privacy rules can be applied too. The contexts are categorized in two sets: system-contexts and classification contexts. The system contexts adapt systems behaviors. The Classification contexts guide COAST to select current classifiers and modify some of them. COAST can work without server to enable autonomic behavior. Clients can connect to peers to achieve more advantages such as: fault-tolerance feature, with severs connection, achieving more contexts from the other clients´ resources.
Keywords
data privacy; speech recognition; text analysis; ubiquitous computing; user interfaces; COAST; context-aware pervasive speech recognition system; context-aware speech to text translator; user privacy rules; Context; Graphical user interfaces; Privacy; classification; context-aware; pervasive; speech recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Wireless and Pervasive Computing (ISWPC), 2011 6th International Symposium on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-9868-0
Electronic_ISBN
978-1-4244-9867-3
Type
conf
DOI
10.1109/ISWPC.2011.5751306
Filename
5751306
Link To Document