资源论文Modelling High-Dimensional Sequences with LSTM-RTRBM: Application to Polyphonic Music Generation

Modelling High-Dimensional Sequences with LSTM-RTRBM: Application to Polyphonic Music Generation

2019-11-20 | |  68 |   33 |   0
Abstract We propose an automatic music generation demo based on artificial neural networks, which integrates the ability of Long Short-Term Memory (LSTM) in memorizing and retrieving useful history information, together with the advantage of Restricted Boltzmann Machine (RBM) in high dimensional data modelling. Our model can generalize to different musical styles and generate polyphonic music better than previous models.

上一篇:Max Order: A Tale of Creativity

下一篇:Capturing a Musician’s Groove: Generation of Realistic Accompaniments from Single Song Recordings

用户评价
全部评价

热门资源

  • Learning to Predi...

    Much of model-based reinforcement learning invo...

  • Stratified Strate...

    In this paper we introduce Stratified Strategy ...

  • The Variational S...

    Unlike traditional images which do not offer in...

  • Learning to learn...

    The move from hand-designed features to learned...

  • A Mathematical Mo...

    Direct democracy, where each voter casts one vo...