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

Abstract

1. 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 and behaviour. Several techniques have been used to quantify song complexity and be broadly categorized into measures of sequential variations and measures of diversity. However, these methods are unable to account for important acoustic features like the frequency bandwidth and the variety in the spectro-temporal shape of notes which are an integral part of these vocal signals. This study proposes a new complexity method that considers intra-song note variability and calculates a weighted index for birdsongs using spectral cross-correlation.2. We first compared previously described methods to understand their advantages and limitations based on the factors that would affect the complexity of songs.We then developed a new method, Note Variability Index (NVI), which incorporates the spectral features of notes to quantify complexity. This method alleviates the need for manual classification of notes that can be error-prone. We used spectrogram cross-correlation to compare notes within a song and used the output values to quantify song complexity.3. To evaluate the efficacy of the new method, we generated synthetic songs to caricature extremes in song complexity and compared selected conventional complexity methods along with the NVI. We provide case-specific limitations of these methods. Additionally, to examine the efficacy of this new method in real-world scenarios, we used natural birdsongs from multiple species across the globe with varying song structures to compare conventional methods with NVI. 4. To our knowledge, NVI is the only song complexity method that captures the variation of spectro-temporal shapes of the notes in songs where the conventional methods fail to distinguish between similar song structures with different note types. Furthermore, as NVI does not need a manual classification of notes, it can be easily implemented for any type of birdsong with existing sound analysis software; it is quick, avoids the possible subjectivity in note classification and can be automated for large datasets.

A cultural atlas of vocal variation: yellow-naped amazons exhibit contact call dialects throughout their Mesoamerican range

“…While SPCC is widely-used method of assessing acoustic similarity (Cortopassi and Bradbury, 2000;Sharp and Hatchwell, 2006;Araya-Salas et al, 2019) and has been used in several previous studies of acoustic variation in parrots (Wright, 1996;Wright et al, 2008), the limits of its capabilities should be considered. The cross-corr function from the package warbleR in R generates correlation coefficients by sliding one spectrogram over another and comparing amplitudes for each frequency and time point across each call (Clark et al, 1987;Araya-Salas and Smith-Vidaurre, 2017;Sawant et al, 2022). Thus, when call types use the same bandwidths and have very similar fundamental frequencies, the cross correlation will indicate that the calls are acoustically similar, even if there are visually detectable temporal and frequency modulation differences in the overall structure (Supplementary Figure 2).…”

Song Richness Index: A measure to understand the diversity and repetition of notes in a birdsong

“…But given the dynamic nature of these songs, it has always been a challenge to have one robust method to quantify the note diversity (Kershenbaum and Garland 2015;Mikula, Petrusková, and Albrecht 2018). Kershenbaum et al (2016) presented various approaches to measuring birdsong complexity which can be categorized into two major groups-measures of sequential variations of notes (order) and measures of the diversity of notes within a song (Sawant et al, 2021). The diversity of birdsongs is often studied in two ways; a) Eventual note diversity-the complexity across songs bouts and b) Immediate note diversity-the complexity within individual song bout.…”

“…The copyright holder for this preprint this version posted December 18, 2021. ; https://doi.org/10.1101/2021.12.18.472638 doi: bioRxiv preprint (Spencer et al 2003;Sawant et al 2021;L. Z. Garamszegi, Balsby, and Bell 2005;Najar and Benedict 2019).…”