Voice Activity Detection Using Wavelet-Based Multiresolution Spectrum and Support Vector Machines and Audio Mixing Algorithm

2006 ◽  
pp. 78-88 ◽  
Author(s):  
Wei Xue ◽  
Sidan Du ◽  
Chengzhi Fang ◽  
Yingxian Ye
Keyword(s):  
Support Vector Machines ◽  
Voice Activity Detection ◽  
Support Vector ◽  
Activity Detection ◽  
Vector Machines ◽  
Audio Mixing ◽  
Voice Activity

Voice activity detection using optimal window overlapping especially over health-care infrastructure

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shilpa Sharma ◽  
Punam Rattan ◽  
Anurag Sharma ◽  
Mohammad Shabaz
Keyword(s):  
Health Care ◽  
Health Care Professionals ◽  
Research Work ◽  
Voice Activity Detection ◽  
Support Vector ◽  
Activity Detection ◽  
Content Type ◽  
Health Care Infrastructure ◽  
Voice Activity ◽  
Optimal Window

Purpose This paper aims to introduce recently an unregulated unsupervised algorithm focused on voice activity detection by data clustering maximum margin, i.e. support vector machine. The algorithm for clustering K-mean used to solve speech behaviour detection issues was later applied, the application, therefore, did not permit the identification of voice detection. This is critical in demands for speech recognition. Design/methodology/approach Here, the authors find a voice activity detection detector based on a report provided by a K-mean algorithm that permits sliding window detection of voice and noise. However, first, it needs an initial detection pause. The machine initialized by the algorithm will work on health-care infrastructure and provides a platform for health-care professionals to detect the clear voice of patients. Findings Timely usage discussion on many histories of NOISEX-92 var reveals the average non-speech and the average signal-to-noise ratios hit concentrations which are higher than modern voice activity detection. Originality/value Research work is original.

scholarly journals Voice Activity Detection Using Fuzzy Entropy and Support Vector Machine

Entropy ◽  
2016 ◽  
Vol 18 (8) ◽  
pp. 298 ◽  
Author(s):  
R. Johny Elton ◽  
P. Vasuki ◽  
J. Mohanalin
Keyword(s):  
Support Vector Machine ◽  
Voice Activity Detection ◽  
Fuzzy Entropy ◽  
Support Vector ◽  
Activity Detection ◽  
Voice Activity

Animal sound activity detection using multi-class support vector machines

2011 ◽  
Author(s):  
W. Astuti ◽  
A. M. Aibinu ◽  
M. J. E Salami ◽  
R. Akmelawati ◽  
Asan G.A Muthalif
Keyword(s):  
Support Vector Machines ◽  
Support Vector ◽  
Activity Detection ◽  
Vector Machines

Improved voice activity detection algorithm using wavelet and support vector machine

2010 ◽  
Vol 24 (3) ◽  
pp. 531-543 ◽  
Author(s):  
Shi-Huang Chen ◽  
Rodrigo Capobianco Guido ◽  
Trieu-Kien Truong ◽  
Yaotsu Chang
Keyword(s):  
Support Vector Machine ◽  
Detection Algorithm ◽  
Voice Activity Detection ◽  
Support Vector ◽  
Activity Detection ◽  
Voice Activity

Voice activity detection based on support vector machine using effective feature vectors

2007 ◽  
Author(s):  
Q-Haing Jo ◽  
Yun-Sik Park ◽  
Kye-Hwan Lee ◽  
Ji-Hyun Song ◽  
Joon-Hyuk Chang
Keyword(s):  
Support Vector Machine ◽  
Voice Activity Detection ◽  
Support Vector ◽  
Activity Detection ◽  
Feature Vectors ◽  
Voice Activity
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