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Poster
in
Workshop: Machine Learning for Audio

ScripTONES: Sentiment-Conditioned Music Generation for Movie Scripts

Vishruth Veerendranath · Vibha Masti · Utkarsh Gupta · Hrishit Chaudhuri · Gowri Srinivasa


Abstract:

Film scores are considered an essential part of the film cinematic experience, but the process of film score generation is often expensive and infeasible for small-scale creators. Automating the process of film score composition would provide useful starting points for music in small projects. In this paper, we propose a two-stage pipeline for generating music from a movie script. The first phase is the Sentiment Analysis phase where the sentiment of a scene from the film script is encoded into the valence-arousal continuous space. The second phase is the Conditional Music Generation phase which takes as input the valence-arousal vector and conditionally generates piano MIDI music to match the sentiment. We study the efficacy of various music generation architectures by performing a qualitative user survey and propose methods to improve sentiment-conditioning in VAE architectures.

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