# Modelling birdsong transmission with methods from molecular sequence analysis

## TL;DR

This paper introduces a novel Markov model inspired by molecular sequence analysis to study birdsong transmission, fitting it with advanced algorithms and analyzing Java sparrow songs, revealing limitations in predictive power due to biological factors.

## Contribution

The paper develops a new Markov model for birdsong transmission based on molecular sequence analysis methods, applying a novel fitting algorithm to real bird song data.

## Key findings

- Limited predictive power of the model for Java sparrow songs.
- Possible reasons include high song learning fidelity and short song length.
- Model provides insights into song transmission dynamics.

## Abstract

In many species of songbirds, juvenile males learn their songs from adult male tutors. In this paper we formulate a novel Markov model for birdsong transmission developed by analogy with models used in biological sequence analysis. We fit the model using the recently developed Interacting Particle Langevin Algorithm (IPLA) of Akyildiz et al. (arXiv:2303.13429) and analyse a collection of songs from Java sparrows (Lonchura oryzivora) originally recorded and studied by Masayo Soma and her collaborators. The model proves to have limited predictive power for a number of natural problems associated with song transmission in Java sparrows and we propose reasons for this, including the well-established faithfulness of song-learning and the comparative brevity of Java sparrow songs.