Variable syllable context depth in Bengalese finch songs: A Bayesian sequence model
Noémi Éltető, Lena Veit, Avani Koparkar, Peter Dayan · COSYNE 2023
Birdsong is an important model for vocal learning and sequential motor behavior. Similarly to human language, songs, notably those of Bengalese finches and canaries, exhibit higher-order sequence structure, meaning that the statistics of one syllable may depend on a number of previous syllables. However, this number (the context depth) varies in a manner that has challenged previous formal approaches. Here we used a hierarchical non-parametric Bayesian sequence model (based on Teh, 2006; Elteto et al., 2022) that seamlessly combines predictive information from shorter and longer contexts of
Sun, Mar 12, 2023