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
相关论文
共 50 条
  • [21] Developing a broadband automatic speech recognition system for Afrikaans
    de Wet, Febe
    de Waal, Alta
    van Huyssteen, Gerhard B.
    12TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2011 (INTERSPEECH 2011), VOLS 1-5, 2011, : 3192 - +
  • [22] Development of Smart Healthcare System Based on Speech Recognition Using Support Vector Machine and Dynamic Time Warping
    Ismail, Ahmed
    Abdlerazek, Samir
    El-Henawy, Ibrahim M.
    SUSTAINABILITY, 2020, 12 (06)
  • [23] On the Design of an Automatic Speech Recognition System for Romanian Language
    Caranica, Alexandru
    Cucu, Horia
    Buzo, Audi
    Burileanu, Corneliu
    CONTROL ENGINEERING AND APPLIED INFORMATICS, 2016, 18 (02): : 65 - 76
  • [24] Applying Nonlinear Techniques for an Automatic Speech Recognition System
    Schiopu, Daniela
    NONLINEAR DYNAMICS OF ELECTRONIC SYSTEMS, 2014, 438 : 371 - 378
  • [25] REFINING AUTOMATIC SPEECH RECOGNITION SYSTEM FOR OLDER ADULTS
    Chen, Liu
    Asgari, Meysam
    2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021), 2021, : 7003 - 7007
  • [26] Grapheme-Based Automatic Speech Recognition Using KL-HMM
    Magimai-Doss, Mathew
    Rasipuram, Ramya
    Aradilla, Guillermo
    Bourlard, Herve
    12TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2011 (INTERSPEECH 2011), VOLS 1-5, 2011, : 452 - 455
  • [27] Evaluating Speech Intelligibility for Cochlear Implants Using Automatic Speech Recognition
    Zhou, Hengzhi
    Shi, Mingyue
    Meng, Qinglin
    2024 IEEE 14TH INTERNATIONAL SYMPOSIUM ON CHINESE SPOKEN LANGUAGE PROCESSING, ISCSLP 2024, 2024, : 1 - 5
  • [28] Using Clinician Annotations to Improve Automatic Speech Recognition of Stuttered Speech
    Heeman, Peter A.
    Lunsford, Rebecca
    McMillin, Andy
    Yaruss, J. Scott
    17TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2016), VOLS 1-5: UNDERSTANDING SPEECH PROCESSING IN HUMANS AND MACHINES, 2016, : 2651 - 2655
  • [29] CLOUD BASED FUZZY HEALTHCARE SYSTEM
    Sundharakumar, K. B.
    Dhivya, S.
    Mohanavalli, S.
    Chander, Vinob R.
    BIG DATA, CLOUD AND COMPUTING CHALLENGES, 2015, 50 : 143 - 148
  • [30] Human beatbox sound recognition using an automatic speech recognition toolkit
    Evain, Solene
    Lecouteux, Benjamin
    Schwab, Didier
    Contesse, Adrien
    Pinchaud, Antoine
    Bernardoni, Nathalie Henrich
    BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2021, 67