May 8, 2020 · The study employs a dynamical statistical model to estimate melodic line surprisal and develops an optimization procedure using parametrized ...

The study employs a dynamical statis- tical model to estimate melodic line surprisal and develops an opti- mization procedure using parametrized codebooks to ...

This work explores listeners' engagement to newly synthesized music and tests the hypothesis that maximizing statistical surprisal would result in increased ...

The study employs a dynamical statis- tical model to estimate melodic line surprisal and develops an opti- mization procedure using parametrized codebooks to ...

Request PDF | On May 1, 2020, Sandeep Kothinti and others published Synthesizing Engaging Music Using Dynamic Models of Statistical Surprisal | Find, ...

Paper Title, SYNTHESIZING ENGAGING MUSIC USING DYNAMIC MODELS OF STATISTICAL SURPRISAL ; Authors, Sandeep Reddy Kothinti, Benjamin Skerritt-Davis, Johns Hopkins ...

Synthesizing engaging music using dynamic models of statistical surprisal. S Kothinti, B Skerritt-Davis, A Nair, M Elhilali. ICASSP 2020-2020 IEEE ...

Apr 25, 2024 · Acoustic Event Detection Using Speaker Recognition Techniques: Model ... Synthesizing Engaging Music Using Dynamic Models of Statistical Surprisal ...

The Dynamic Regularity Extraction (D-REX) model is a computational model for predictive processing in auditory perception of sequential sounds.

Synthesizing Engaging Music Using Dynamic Models of Statistical Surprisal · Conference Paper. May 2020. ·. 23 Reads. ·. 1 Citation. Sandeep Reddy Kothinti.