3 papers
cs.SD2025
Estimating Musical Surprisal from Audio in Autoregressive Diffusion Model Noise Spaces
Mathias Rose Bjare, Stefan Lattner, Gerhard Widmer
Recently, the information content (IC) of predictions from a Generative Infinite-Vocabulary Transformer (GIVT) has been used to model musical expectancy and surprisal in audio. We…
cs.SD2025
Estimating Musical Surprisal in Audio
Mathias Rose Bjare, Giorgia Cantisani, Stefan Lattner +1
In modeling musical surprisal expectancy with computational methods, it has been proposed to use the information content (IC) of one-step predictions from an autoregressive model a…
cs.SD2022
On the Typicality of Musical Sequences
Mathias Rose Bjare, Stefan Lattner
It has been shown in a recent publication that words in human-produced English language tend to have an information content close to the conditional entropy. In this paper, we show…