Generating Music with a Self-Correcting Non-Chronological Autoregressive Model

• URL: http://arxiv.org/abs/2008.08927v1
• Date: Tue, 18 Aug 2020 20:36:47 GMT
• Title: Generating Music with a Self-Correcting Non-Chronological Autoregressive Model
• Authors: Wayne Chi, Prachi Kumar, Suri Yaddanapudi, Rahul Suresh, Umut Isik
• Abstract summary: We describe a novel approach for generating music using a self-correcting, non-chronological, autoregressive model. We represent music as a sequence of edit events, each of which denotes either the addition or removal of a note. During inference, we generate one edit event at a time using direct ancestral sampling.
• Score: 6.289267097017553
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We describe a novel approach for generating music using a self-correcting, non-chronological, autoregressive model. We represent music as a sequence of edit events, each of which denotes either the addition or removal of a note---even a note previously generated by the model. During inference, we generate one edit event at a time using direct ancestral sampling. Our approach allows the model to fix previous mistakes such as incorrectly sampled notes and prevent accumulation of errors which autoregressive models are prone to have. Another benefit is a finer, note-by-note control during human and AI collaborative composition. We show through quantitative metrics and human survey evaluation that our approach generates better results than orderless NADE and Gibbs sampling approaches.

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