Recent Submissions

  • Automatic Transcription of Vocal Quartets 

    BENETOS, E; Schramm,, R; DMRN+11: Digital Music Research Network One-day Workshop 2016 (Centre for Digital Music, Queen Mary University of London, 2016-12-20)
    This work presents a probabilistic latent component analysis (PLCA) method applied to automatic music transcription of a cappella performances of vocal quartets. A variable-Q transform (VQT) representation of the audio ...
  • Intelligent Audio Mixing Using Deep Learning 

    MARTINEZ RAMIREZ, MA; Reiss, J; DMRN+11: Digital Music Research Network One-day Workshop 2016 (Centre for Digital Music, Queen Mary University of London, 2016-12)
    We propose a research trajectory in the field of deep learning applied to music production systems such as mixing, mastering, sound design and sound synthesis.
  • Perceptual Evaluation of Synthesised Sound Effects 

    MOFFAT, DJ; Reiss, J; DMRN+11: Digital Music Research Network One-day Workshop 2016 (Centre for Digital Music, Queen Mary University of London, 2016-12)
    Sound synthesis is the method of artificially producing sounds. A range of sound effects were generated through the use of five different synthesis techniques, across eight sound classes to produce sixty six different ...
  • Explaining Predictions of Machine Listening Systems 

    MISHRA, S; Sturm, B; Dixon, S; DMRN+11: Digital Music Research Network One-day Workshop 2016 (Centre for Digital Music, Queen Mary University of London, 2016-12)
    We adapt local, interpretable and model-agnostic explanations [1] for use with a machine listening system, and demonstrate it for singing voice detection. Such explanations provide ways to understand the behaviour of machine ...
  • Towards a Music Language Model for Audio Analysis 

    YCART, A; Benetos, E; DMRN+11: Digital Music Research Network One-day Workshop 2016 (Centre for Digital Music, Queen Mary University of London, 2016-12)
    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 ...
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