Abstract
The Bengalese finch song has been widely studied for its unique features and similarity to human language. For com-putational analysis the songs must be represented in songnote sequences. An automated approach for this purpose is highly desired since manual processing makes human annotation cumbersome, and human annotation is very heu-ristic and easily lacks objectivity. In this paper, we propose a new approach for automatic detection and recognition of the songnote sequences via image processing. The proposed method is based on human recognition process to visually identify the patterns in a sonogram image. The songnotes of the Bengalese finch are dependent on the birds and similar pattern does not exist in two different birds. Considering this constraint, our experiments on real birdsong data of different Bengalese finch show high accuracy rates for automatic detection and recognition of the songnotes. These results indicate that the proposed approach is feasible and generalized for any Bengalese finch songs.
Highlights
Birdsong has been actively studied via analysis of songnote sequences to understand the language model of birds
The Bengalese finch song has been widely studied for its unique features and similarity to human language
We propose a new approach for automatic detection and recognition of the songnote sequences via image processing
Summary
Birdsong has been actively studied via analysis of songnote sequences to understand the language model of birds. Bengalese finch songs have been studied as a model of human language. According to the recent studies, the courtship songs of Bengalese finches have unique features and similarity with a human language [2]. Acoustic song analysis is necessary to find the song elements and their sequence for carrying out an analysis to understand the song syntax [3] and the learning process of the song. Previous studies that employed sound processing had drawbacks as an automated approach. This paper introduces a new generalized approach that employs image processing to overcome the drawbacks
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: Journal of Intelligent Learning Systems and Applications
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.