An Approach for TV Channel Recognition based on Audio

DOI

10.2991/iccmcee-15.2015.32How to use a DOI?

Keywords

Audio Features; TV Channel Recognition; sequence alignment; Tolerance Processing; Pairwise Point Checking

Abstract

In order to amalgamate distributing platform of traditional TV program with mobile Internet on technology and business, it is necessary to study the method of TV channel recognition based on the collaboration between mobile terminals and publishing service of TV program. Due to some advantages based on audio features, such as less processing data volume, lower complexity of signal variation, better realtime performance and non-directional sampling, some processing steps, such as data denoising, data standardization processing, sequence alignment, tolerance processing and pairwise point checking, etc., are studied for TV channel recognition based on audio features. The experimental results show that the overall performance of the proposed approach is better than those based on frequency domain and based on time domain simply because it has some advantages such as reduction of both sampling difference and sampling environment interference for various of handheld mobile terminals, reduction of transmitting interference for content distributing server-side, excellent overall performance on accuracy and efficiency, etc. The proposed approach can also be applied into data pushing, user interactive discussion, realtime vote, etc.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - LiJin Long
PY  - 2015/11
DA  - 2015/11
TI  - An Approach for TV Channel Recognition based on Audio
BT  - Proceedings of the 2015 4th International Conference on Computer, Mechatronics, Control and Electronic Engineering
PB  - Atlantis Press
SP  - 171
EP  - 178
SN  - 2352-5401
UR  - https://doi.org/10.2991/iccmcee-15.2015.32
DO  - 10.2991/iccmcee-15.2015.32
ID  - Long2015/11
ER  -