NDLI: Automatic speech recognition using interlaced derivative pattern for cloud based healthcare system

Content Provider	Springer Nature Link
Author	Muhammad, Ghulam
Copyright Year	2015
Abstract	Cloud computing brings several advantages such as flexibility, scalability, and ubiquity in terms of data acquisition, data storage, and data transmission. This can help remote healthcare among other applications in a great deal. This paper proposes a cloud based framework for speech enabling healthcare. In the proposed framework, the patients or any healthy person seeking for some medical assistance can send his/her request by speech commands. The commands are managed and processed in the cloud server. Any doctor with proper authentication can receive the request. By analyzing the request, the doctor can assist the patient or the person. This paper also proposes a new feature extraction technique, namely, interlaced derivative pattern (IDP), to automatic speech recognition (ASR) system to be deployed into the cloud server. The IDP exploits the relative Mel-filter bank coefficients along different neighborhood directions from the speech signal. Experimental results show that the proposed IDP-based ASR system performs reasonably well even when the speech is transmitted via smart phones.
Starting Page	795
Ending Page	802
Page Count	8
File Format	PDF
ISSN	13867857
Journal	Cluster Computing
Volume Number	18
Issue Number	2
e-ISSN	15737543
Language	English
Publisher	Springer US
Publisher Date	2015-02-08
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Automatic speech recognition Interlaced derivative pattern Cloud computing Healthcare Processor Architectures Operating Systems Computer Communication Networks
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Software

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