Co-creativity in music refers to two or more musicians or musical agents interacting with one another by composing or improvising music. However, this is a very subjective process and each musician has their own preference as to which improvisation is better for some context. In this paper, we aim to create a measure based on total information flow to quantitatively evaluate the co-creativity process in music. In other words, our measure is an indication of how "good" a creative musical process is. Our main hypothesis is that a good musical creation would maximize information flow between the participants captured by music voices recorded in separate tracks. We propose a method to compute the information flow using pre-trained generative models as entropy estimators. We demonstrate how our method matches with human perception using a qualitative study.

翻译：音乐中的共同创造力指两位或多位音乐家或音乐代理通过作曲或即兴演奏进行互动。然而，这是一个非常主观的过程，每位音乐家对于何种即兴演奏在特定情境下更优有各自偏好。本文旨在基于总信息流创建一种度量方法，以定量评估音乐中的共同创造力过程。换言之，我们的度量指标用于表征创造性音乐过程的“优良”程度。核心假设是：优质音乐创作会最大化参与者之间通过独立音轨录制的音乐声部所捕获的信息流。我们提出一种利用预训练生成模型作为熵估计器来计算信息流的方法，并通过定性研究证明我们的方法与人类感知的一致性。