Listeners' expectations for melodies and harmonies in tonal music are perhaps the most
studied aspect of music cognition. Long debated has been whether faster response times …

We introduce a method for imposing higher-level structure on generated, polyphonic music.
A Convolutional Restricted Boltzmann Machine (C-RBM) as a generative model is combined …

For more than a decade, music information science and musicology have been at what
Nicholas Cook has described as a'moment of opportunity'for collaboration on database …

Intuitively, music has both predictable and unpredictable components. In this paper, we
assess this qualitative statement in a quantitative way using common time series models …

In this paper, we propose a rhythmically informed method for onset detection in polyphonic
music. Music is highly structured in terms of the temporal regularity underlying onset …

Guided by the idea that musical human-computer interaction may become more effective,
intuitive, and creative when basing its computer part on cognitively more plausible learning …

Machine listening and machine learning are critical aspects in seeking a heightened
musical agency for new interactive music systems. This paper details LL …

In this paper we present a system that learns rhythmic patterns from drum audio recording
and synthesizes music variations from the learnt sequence. The procedure described is …

This work focuses on the automatic identification of musical piece versions (alternate
renditions of the same musical composition like cover songs, live recordings, remixes, etc.) …

A system is presented that learns the structure of an audio recording of a rhythmical
percussion fragment in an unsupervised manner and that synthesizes musical variations …