Now showing items 1-10 of 10
Digital Music Lab: A Framework for Analysing Big Music Data
Towards a Music Language Model for Audio Analysis
(Centre for Digital Music, Queen Mary University of London, 2016-12-20)
Polyphonic Automatic Music Transcription remains a challenging problem. Many studies focus on the extraction of features from audio signals; we focus here on Music Language Models that help turn those features into a ...
Classification-based Note Tracking for Automatic Music Transcription
Note tracking constitutes a key process in Automatic Music Transcription as it derives a note-level transcription from a frame-based pitch activation representation. While this stage is commonly performed using a set of ...
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 ...
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 ...
The Sousta corpus: Beat-informed automatic transcription of traditional dance tunes
In this paper, we present a new corpus for research in computational ethnomusicology and automatic music transcription, consisting of traditional dance tunes from Crete. This rich dataset includes audio recordings, scores ...