Recent Submissions

  • Transfer learning for music classification and regression tasks 

    CHOI, K; FAZEKAS, G; SANDLER, M; kyunghyun, C; The 18th International Society of Music Information Retrieval (ISMIR) Conference (International Society of Music Information, 2017)
    In this paper, we present a transfer learning approach for music classification and regression tasks. We propose to use a pre-trained convnet feature, a concatenated feature vector using the activations of feature maps ...
  • Polyphonic Music Sequence Transduction with Meter-Constrained LSTM Networks 

    YCART, A; BENETOS, E; IEEE International Conference on Acoustics, Speech and Signal Processing (IEEE International Conference on Acoustics, Speech and Signal Processing, 2018)
    Automatic transcription of polyphonic music remains a challenging task in the field of Music Information Retrieval. In this paper, we propose a new method to post-process the output of a multi-pitch detection model using ...
  • A supervised approach for rhythm transcription based on tree series enumeration 

    Ycart, A; Jacquemard, F; Bresson, J; Staworko, S (ICMC 2016 - 42nd International Computer Music Conference, 2018-01)
    We present a rhythm transcription system integrated in the computer-assisted composition environment OpenMusic. Rhythm transcription consists in translating a series of dated events into traditional music notation's pulsed ...
  • A Functional Taxonomy of Music Generation Systems 

    Herremans, D; Chuan, C-H; Chew, E (Association for Computing Machinery, 2017-11)
    Digital advances have transformed the face of automatic music generation since its beginnings at the dawn of computing. Despite the many breakthroughs, issues such as the musical tasks targeted by different machines and ...
  • MorpheuS: generating structured music with constrained patterns and tension 

    Herremans, D; Chew, E (IEEE, 2017-08)
    Automatic music generation systems have gained in popularity and sophistication as advances in cloud computing have enabled large-scale complex computations such as deep models and optimization algorithms on personal ...
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