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Music Informatics Group

Georgia Institute of Technology

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  • Evaluation of Generative Models in Music
  • EAsT: Embeddings As Teachers for Music Classification
  • Latte: Cross-framework Python Package for Evaluation of Latent-Based Generative Models
  • Score-Informed Networks for Music Performance Assessment
  • Multi-Task Learning for Instrument Activation Aware Music Source Separation
  • AR-VAE: Attribute-based Regularization of VAE Latent Spaces
  • dMelodies: A Music Dataset for Disentanglement Learning
  • Learning to Traverse Latent Spaces for Musical Score Inpainting
  • An Attention Mechanism for Musical Instrument Recognition
  • Explicitly Conditioned Melody Generation

Recent Posts

  • Evaluation of Generative Models in Music
  • EAsT: Embeddings As Teachers for Music Classification
  • Latte: Cross-framework Python Package for Evaluation of Latent-Based Generative Models
  • Score-Informed Networks for Music Performance Assessment
  • Multi-Task Learning for Instrument Activation Aware Music Source Separation

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    Neural Style Transfer in Music

    Read a recent blog post by our PhD student Ashis Pati on the difficulties on style transfer in music as opposed to pictures.

    Posted on January 11, 2018January 11, 2018Author AlexanderCategories gtcmt, project

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