Finding, visualizing, and quantifying latent structure across diverse animal vocal repertoires
Fig 13
Latent comparisons of hand- and algorithmically-clustered Bengalese finch song.
A-G are from a dataset produced by Nicholson et al., [9] and H-N are from a dataset produced by Koumura et al., [10] (A,H) UMAP projections of syllables of Bengalese finch song, colored by hand labels. (B,I) Algorithmic labels (UMAP/HDBSCAN). (C, J) Transitions between syllables, where color represents time within a bout of song. (D,K) Comparing the transitions between elements from a single hand-labeled category that comprises multiple algorithmically labeled clusters. Each algorithmically labeled cluster and the corresponding incoming and outgoing transitions are colored. Transitions to different regions of the UMAP projections demonstrate that the algorithmic clustering method finds clusters with different syntactic roles within hand-labeled categories. (E,L) Markov model from hand labels colored the same as in (A,H) (F,M) Markov model from clustered labels, colored the same as in (B,I). (G,N) Examples of syllables from multiple algorithmic clusters falling under a single hand-labeled cluster. Colored bounding boxes around each syllable denotes the color category from (D,K).