A Feasible Approach for Automatic Detection and Recognition of the Bengalese Finch Songnotes and Their Sequences

The Bengalese finch song has been widely studied for its unique features and similarity to human language. For computational 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 heuristic 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.