Search Results for author: Monica Dinculescu

Found 4 papers, 1 papers with code

Encoding Musical Style with Transformer Autoencoders

no code implementations ICML 2020 Kristy Choi, Curtis Hawthorne, Ian Simon, Monica Dinculescu, Jesse Engel

We consider the problem of learning high-level controls over the global structure of generated sequences, particularly in the context of symbolic music generation with complex language models.

Music Generation

The Bach Doodle: Approachable music composition with machine learning at scale

no code implementations14 Jul 2019 Cheng-Zhi Anna Huang, Curtis Hawthorne, Adam Roberts, Monica Dinculescu, James Wexler, Leon Hong, Jacob Howcroft

To make music composition more approachable, we designed the first AI-powered Google Doodle, the Bach Doodle, where users can create their own melody and have it harmonized by a machine learning model Coconet (Huang et al., 2017) in the style of Bach.

BIG-bench Machine Learning Quantization

Music Transformer

12 code implementations ICLR 2019 Cheng-Zhi Anna Huang, Ashish Vaswani, Jakob Uszkoreit, Noam Shazeer, Ian Simon, Curtis Hawthorne, Andrew M. Dai, Matthew D. Hoffman, Monica Dinculescu, Douglas Eck

This is impractical for long sequences such as musical compositions since their memory complexity for intermediate relative information is quadratic in the sequence length.

Music Generation Music Modeling

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