Acoustic Event Classification using MFCC and MP Algorithm
Gunavathi
, Geethesh , Leora Dsouza , Mohammad Rizwan Khader , Sunil B.N
MFCC, MP algorithm, classification, feature extraction
This paper presents our experiments on acoustic scene classification. Classification of acoustic scene to extract the audio features is a tough task because of the diversity in their nature. Extracting the appropriate features is an important task for increasing the efficiency of the classification. Using MFCC features alone will not achieve a maximum efficiency in characterization of acoustic scenes. Here we use MFCC algorithm along with MP Algorithm to classify the acoustic scenes. Here we use Support Vector Machine Algorithm to train the machine. Classifier model is built using libSVM for training samples and the machine is then able to recognize various acoustic Scenes. Results shows that Acoustic scene classification achieves better accuracy when MP algorithm is used along with MFCC.
"Acoustic Event Classification using MFCC and MP Algorithm", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.2, Issue 5, page no.28 - 31, April-2017, Available :https://ijsdr.org/papers/IJSDR1705006.pdf
Volume 2
Issue 5,
April-2017
Pages : 28 - 31
Paper Reg. ID: IJSDR_170246
Published Paper Id: IJSDR1705006
Downloads: 000347040
Research Area: Engineering
Country: dakshina kannada, karnataka, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave