Now showing items 1-9 of 9
An End-to-End Neural Network for Polyphonic Piano Music Transcription
We present a supervised neural network model for polyphonic piano music transcription. The architecture of the proposed model is analogous to speech recognition systems and comprises an acoustic model and a music language ...
Explaining Predictions of Machine Listening Systems
(Centre for Digital Music, Queen Mary University of London, 2016-12-20)
We adapt local, interpretable and model-agnostic explanations  for use with a machine listening system, and demonstrate it for singing voice detection. Such explanations provide ways to understand the behaviour of machine ...
An attack/decay model for piano transcription
We demonstrate that piano transcription performance for a known piano can be improved by explicitly modelling piano acoustical features. The proposed method is based on non-negative matrix factorisation, with the following ...
Learning a feature space for similarity in world music
In this study we investigate computational methods for assessing music similarity in world music styles. We use state-of-the-art audio features to describe musical content in world music recordings. Our music collection ...