Spectrogram cross?correlation can be used to measure the complexity of bird vocalizations

Birdsong is an important signal in mate attraction and territorial defence. Quantifying the complexity of these songs can shed light on individual fitness, sexual selection behaviour. Several techniques have been used to quantify song be broadly categorized into measures sequential variations diversity. However, methods are unable account for acoustic features like frequency bandwidth variety spectro-temporal shape notes which integral part vocal signals. This study proposes a new method that considers intra-song note variability calculates weighted index birdsongs using spectral cross-correlation. We first compared previously described understand their advantages limitations based factors would affect songs. then developed method, Note Variability Index (NVI), incorporates complexity. alleviates need manual classification error-prone. spectrogram cross-correlation compare within output values To evaluate efficacy we generated synthetic caricature extremes selected conventional along with NVI. provide case-specific methods. Additionally, examine this real-world scenarios, natural from multiple species across globe varying structures our knowledge, NVI only captures variation shapes where fail distinguish between similar different types. Furthermore, as does not notes, it easily implemented any type birdsong existing sound analysis software; quick, avoids possible subjectivity automated large datasets.