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

被引:61
作者
Muhammad, Ghulam [1 ]
机构
[1] King Saud Univ, Dept Comp Engn, Coll Comp & Informat Sci, Riyadh, Saudi Arabia
来源
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS | 2015年 / 18卷 / 02期
关键词
Automatic speech recognition; Interlaced derivative pattern; Cloud computing; Healthcare;
D O I
10.1007/s10586-015-0439-7
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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 Melfilter 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.
引用
收藏
页码:795 / 802
页数:8
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