DocumentCode :
2131312
Title :
A cloud computing service for fast audio source signal separation
Author :
Liang, Tyng-Yeu ; Wang, Ti-Hsin ; Chou, Meng-Te ; Chen, Shiou-Wen
Author_Institution :
Dept. of Electr. Eng., Nat. Kaohsiung Univ. of Appl. Sci., Kaohsiung, Taiwan
fYear :
2011
fDate :
18-21 Sept. 2011
Firstpage :
1
Lastpage :
6
Abstract :
In this study, we propose a cloud computing service for fast audio source signal separation. To implement this service, we have developed a GPU-based ICA (Independent Component Analysis) program by using CUDA software development toolkit (SDK). This program can rapidly separate n independent components from m sources which are composed of these components mixed by a random way. On the other hand, we also have implemented a web server to provide users with the service of fast audio signal separation. Users can upload their audio files onto this web server through the browser interface. After users click the execution command button in the web page, the web server will invoke the GPU-based ICA program to fast separate the independent audio signals from the uploaded files. Finally, users can download and play the wave files of the separated audio signals from the web server by clicking the hyperlink in the website.
Keywords :
Web sites; audio signal processing; cloud computing; computer graphic equipment; coprocessors; independent component analysis; software engineering; source separation; GPU-based ICA program; SDK; Web server; Website; audio source signal separation; browser interface; cloud computing service; independent component analysis; software development toolkit; Graphics processing unit; Independent component analysis; Instruction sets; Kernel; Source separation; Vectors; Web servers; CUDA; Cloud computing; GPU; audio source separation; independent component analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning for Signal Processing (MLSP), 2011 IEEE International Workshop on
Conference_Location :
Santander
ISSN :
1551-2541
Print_ISBN :
978-1-4577-1621-8
Electronic_ISBN :
1551-2541
Type :
conf
DOI :
10.1109/MLSP.2011.6064556
Filename :
6064556
Link To Document :
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