{"ID":5935657,"CreatedAt":"2026-07-07T01:22:02.77346169Z","UpdatedAt":"2026-07-07T02:10:06.972658124Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2607.03496","arxiv_id":"2607.03496","title":"Trajectory Variance: AnUnsupervised Measure of Developmental Vocal Plasticity in Birdsong","abstract":"How much does a vocalization change over the course of development? We propose trajectory variance, a per-vocalization plasticity score that answers this question without type labels. A displacement model learns to predict age-conditioned shifts in autoencoder latent space; the variance of its predictions across target ages quantifies how much each vocalization would change if produced at different developmental stages. Evaluated on three zebra finches (183K-274K vocalizations, 40-101 days post-hatch), trajectory variance separates learned song syllables from innate calls (Cohen's d = 0.29-0.57, AUC = 0.58-0.67, after controlling for duration), while no nonparametric baseline achieves consistent separation. Trajectory variance also correlates with spectral flatness across all three birds (r = -0.48 to -0.75): more plastic vocalizations tend to have more tonal, structured spectra.","short_abstract":"How much does a vocalization change over the course of development? We propose trajectory variance, a per-vocalization plasticity score that answers this question without type labels. A displacement model learns to predict age-conditioned shifts in autoencoder latent space; the variance of its predictions across target...","url_abs":"https://arxiv.org/abs/2607.03496","url_pdf":"https://arxiv.org/pdf/2607.03496v1","authors":"[\"Kanghwi Lee\"]","published":"2026-07-03T17:05:06Z","proceeding":"cs.SD","tasks":"[\"cs.SD\",\"eess.AS\"]","methods":"[]","has_code":false}