DocumentCode :
1857948
Title :
CSR: A Cloud-Assisted Speech Recognition Service for Personal Mobile Device
Author :
Chang, Yu-Shuo ; Hung, Shih-Hao ; Wang, N.J.C. ; Bor-Shen Lin
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Taiwan Univ., Taipei, Taiwan
fYear :
2011
fDate :
13-16 Sept. 2011
Firstpage :
305
Lastpage :
314
Abstract :
Automatic speech recognition (ASR) is a technology which converts the phrases or words spoken by human into text. As a mature technology, ASR has become an alternative input method on many mobile devices, complementing the other input methods operated by hands. Although the technology has been developed for years, the accuracy and computational complexity of ASR have prohibited ASR from being used as the primary input method on mobile devices. While speaker-dependent ASR (SD-ASR) technologies may be used to improve the recognition accuracy, the user is often reluctant to take a time-consuming training process needed to enable SD-ASR for each device. To overcome these problems, we propose a cloud-assisted speech recognition service and its infrastructural design, called CSR, which utilizes servers in the cloud to accelerate ASR, integrates SD-ASR technologies to improve the accuracy of ASR, and populate SD information to enable SD-ASR on multiple mobile device. We have built a prototype to observe the benefits of the CSR service and the issues in load balance, power consumption, and privacy on the client and the server. We show that the CSR service offers fast responses, good accuracy, high availability and good scalability in serving many concurrent users.
Keywords :
cloud computing; mobile radio; speech recognition; automatic speech recognition; cloud-assisted speech recognition service; personal mobile device; speaker-dependent ASR technology; Databases; Hidden Markov models; Mobile handsets; Servers; Silicon; Speech recognition; Training; cloud service; distributed speech recognition; mobile device; pervasive applications;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel Processing (ICPP), 2011 International Conference on
Conference_Location :
Taipei City
ISSN :
0190-3918
Print_ISBN :
978-1-4577-1336-1
Electronic_ISBN :
0190-3918
Type :
conf
DOI :
10.1109/ICPP.2011.23
Filename :
6047199
Link To Document :
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