Are Nearby Neighbors Relatives?: Testing Deep Music Embeddings

Deep neural networks have frequently been used to directly learn representations useful for a given task from raw input data. In terms of overall performance metrics, machine learning solutions employing deep representations frequently have been reported to greatly outperform those using hand-crafted feature representations. At the same time,...

Transfer Learning of Artist Group Factors to Musical Genre Classification

The automated recognition of music genres from audio information is a challenging problem, as genre labels are subjective and noisy. Artist labels are less subjective and less noisy, while certain artists may relate more strongly to certain genres. At the same time, at prediction time, it is not guaranteed that artist labels are available for a...

Music in newspapers: Interdisciplinary opportunities and data-related challenges

Over the past millennia, music has actively been performed and listened to by mankind, thus also playing an important role in establishing sociocultural identities that have evolved over time. In parallel, for many centuries, newspapers played an important role in informing society on a regular and frequent basis on topics noteworthy at that...

Multifaceted Approaches to Music Information Retrieval

Music is a multifaceted phenomenon: beyond addressing our auditory channel, the consumption of music triggers further senses. Also in creating and communicating music, multiple modalities are at play. Next to this, it allows for various ways of interpretation: the same musical piece can be performed in different valid ways, and audiences can in...

Mass Media Musical Meaning: Opportunities from the Collaborative Web

In the digital domain, music is usually studied from a positivist viewpoint, focusing on general ‘objective’ music descriptors. In this work, we strive to put music in a more social and cultural context, looking into ways to unify data analysis methods with thoughts from the humanities on musical meaning and significance. More specifically, we...