A Framework for Automated Pop-song Melody Generation with Piano Accompaniment Arrangement
This addresses the problem of automating music composition for pop songs, offering a tool for musicians or producers, but it is incremental as it builds on existing methods like ARMA and compares to commercial software.
The authors tackled automated pop-song melody generation and piano accompaniment arrangement by proposing a framework that transforms chord progressions into structured melodies and integrated accompaniments using seasonal ARMA processes. Experimental results showed that generated melodies were rated significantly higher than those from bi-directional LSTM, and accompaniment arrangements were comparable to a state-of-the-art commercial software.
We contribute a pop-song automation framework for lead melody generation and accompaniment arrangement. The framework reflects the major procedures of human music composition, generating both lead melody and piano accompaniment by a unified strategy. Specifically, we take chord progression as an input and propose three models to generate a structured melody with piano accompaniment textures. First, the harmony alternation model transforms a raw input chord progression to an altered one to better fit the specified music style. Second, the melody generation model generates the lead melody and other voices (melody lines) of the accompaniment using seasonal ARMA (Autoregressive Moving Average) processes. Third, the melody integration model integrates melody lines (voices) together as the final piano accompaniment. We evaluate the proposed framework using subjective listening tests. Experimental results show that the generated melodies are rated significantly higher than the ones generated by bi-directional LSTM, and our accompaniment arrangement result is comparable with a state-of-the-art commercial software, Band in a Box.