Audio classification based on content features
Other Title(s)
تصنيف الصوت استنادا إلى ميزات المحتوى
Source
Journal of the College of Education for Women
Issue
Vol. 28, Issue 5 (31 Dec. 2017), pp.1415-1423, 9 p.
Publisher
University of Baghdad College of Education for Women
Publication Date
2017-12-31
Country of Publication
Iraq
No. of Pages
9
Main Subjects
Abstract EN
Audio classification is the process to classify different audio types according to contents.
It is implemented in a large variety of real world problems, all classification applications allowed the target subjects to be viewed as a specific type of audio and hence, there is a variety in the audio types and every type has to be treatedcarefully according to its significant properties.Feature extraction is an important process for audio classification.
This workintroduces several sets of features according to the type, two types of audio (datasets) were studied.
Two different features sets are proposed: (i) firstorder gradient feature vector, and (ii) Local roughness feature vector, the experimentsshowed that the results are competitive to those gotten from other popular methods inthis field, such as Zero Crossing Rate (ZCR), Amplitude Descriptor (AD), Short Time Energy (STE), and Volume (Vo).
The test results indicated, that the attained averageaccuracy of classification is improved up to94.9232% for training set and 95.8666%for testing set.The classification performance of these two extracted featuresets is studied individually, and then they used together as one feature set.
Theiroverall performance is investigated, the test results showed that the proposed methods give high classification rates for the audio.
American Psychological Association (APA)
Abd al-Salam, Iyad Abd Abd al-Qahhar. 2017. Audio classification based on content features. Journal of the College of Education for Women،Vol. 28, no. 5, pp.1415-1423.
https://search.emarefa.net/detail/BIM-810831
Modern Language Association (MLA)
Abd al-Salam, Iyad Abd Abd al-Qahhar. Audio classification based on content features. Journal of the College of Education for Women Vol. 28, no. 5 (2017), pp.1415-1423.
https://search.emarefa.net/detail/BIM-810831
American Medical Association (AMA)
Abd al-Salam, Iyad Abd Abd al-Qahhar. Audio classification based on content features. Journal of the College of Education for Women. 2017. Vol. 28, no. 5, pp.1415-1423.
https://search.emarefa.net/detail/BIM-810831
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 1422-1423
Record ID
BIM-810831