alexa FFT and Wavelet-Based Feature Extraction for Acoustic Audio Classification. | OMICS International | Abstract
ISSN: 2277-1891

International Journal of Advance Innovations, Thoughts & Ideas
Open Access

OMICS International organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations
700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)

Research Article

FFT and Wavelet-Based Feature Extraction for Acoustic Audio Classification.

A.K.M Fazlul Haque*

Department of Electronics and Telecommunication Engineering, Daffodil International University

*Corresponding Author:
A.K.M Fazlul Haque
Department of Electronics and Telecommunication Engineering
Daffodil International University
E-mail: [email protected]

Abstract

Speech is one of the vital signals of acoustic classification. Speech recognition is also significant and very well known of audio processing. Speech contains very important frequency information of human being. The features of Audio, especially speech signal may be extracted using FFT (Fast Fourier Transform) and Wavelet to detect the frequency information of the signal. But it is difficult to extract the changes of small variation of speech signal with time-varying morphological characteristics. So, it is needed to be extracted by signal processing method because there are not visible of graphical audio signal. In this paper, an improved wavelet method has been proposed to extract the precise detection of small abnormalities of both original and noise corrupted speech signal which are taken empirically by writing MATLAB program. The proposed wavelet method found to be more summarized over conventional FFT and Wavelet in finding the small abnormalities of audio signal.

Peer Reviewed Journals
 
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2018-19
 
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

Agri & Aquaculture Journals

Dr. Krish

[email protected]

+1-702-714-7001Extn: 9040

Biochemistry Journals

Datta A

[email protected]

1-702-714-7001Extn: 9037

Business & Management Journals

Ronald

[email protected]

1-702-714-7001Extn: 9042

Chemistry Journals

Gabriel Shaw

[email protected]

1-702-714-7001Extn: 9040

Clinical Journals

Datta A

[email protected]

1-702-714-7001Extn: 9037

Engineering Journals

James Franklin

[email protected]

1-702-714-7001Extn: 9042

Food & Nutrition Journals

Katie Wilson

[email protected]

1-702-714-7001Extn: 9042

General Science

Andrea Jason

[email protected]

1-702-714-7001Extn: 9043

Genetics & Molecular Biology Journals

Anna Melissa

[email protected]

1-702-714-7001Extn: 9006

Immunology & Microbiology Journals

David Gorantl

[email protected]

1-702-714-7001Extn: 9014

Materials Science Journals

Rachle Green

[email protected]

1-702-714-7001Extn: 9039

Nursing & Health Care Journals

Stephanie Skinner

[email protected]

1-702-714-7001Extn: 9039

Medical Journals

Nimmi Anna

[email protected]

1-702-714-7001Extn: 9038

Neuroscience & Psychology Journals

Nathan T

[email protected]

1-702-714-7001Extn: 9041

Pharmaceutical Sciences Journals

Ann Jose

[email protected]

1-702-714-7001Extn: 9007

Social & Political Science Journals

Steve Harry

[email protected]

1-702-714-7001Extn: 9042

 
© 2008- 2018 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version
Leave Your Message 24x7