|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 120 - Issue 16 |
| Published: June 2015 |
| Authors: Ajay Kadam, Ramesh M. Kagalkar |
10.5120/21314-4297
|
Ajay Kadam, Ramesh M. Kagalkar . Audio Scenarios Detection Technique. International Journal of Computer Applications. 120, 16 (June 2015), 33-37. DOI=10.5120/21314-4297
@article{ 10.5120/21314-4297,
author = { Ajay Kadam,Ramesh M. Kagalkar },
title = { Audio Scenarios Detection Technique },
journal = { International Journal of Computer Applications },
year = { 2015 },
volume = { 120 },
number = { 16 },
pages = { 33-37 },
doi = { 10.5120/21314-4297 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2015
%A Ajay Kadam
%A Ramesh M. Kagalkar
%T Audio Scenarios Detection Technique%T
%J International Journal of Computer Applications
%V 120
%N 16
%P 33-37
%R 10.5120/21314-4297
%I Foundation of Computer Science (FCS), NY, USA
The proposed research objective is to add to a framework for programmed recognition of sound. In this framework the real errand is to distinguish any information sound stream investigate it & anticipate the likelihood of diverse sounds show up in it. To create and industrially conveyed an adaptable sound web crawler a flexible sound search engine. The calculation is clamor and contortion safe, computationally productive, and hugely adaptable, equipped for rapidly recognizing a short portion of sound stream caught through a phone microphone in the presence of frontal area voices and other predominant commotion, and through voice codec pressure, out of a database of over accessible tracks. The algorithm utilizes a combinatorial hashed time-recurrence group of stars examination of the sound, yielding ordinary properties, for example, transparency, in which numerous tracks combined may each be distinguished.