# Tr"aumerAI: Dreaming Music with StyleGAN

arXiv: https://arxiv.org/abs/2102.04680 · HTML: https://mlsanity.com/paper/2102.04680/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 15 references that are in the map.
- First posted on arXiv 9 Feb 2021.

## Builds on (most cited first, 6 of 6)

- [A Style-Based Generator Architecture for Generative Adversarial Networks](https://mlsanity.com/paper/1812.04948/) (2018)
- [Analyzing and Improving the Image Quality of StyleGAN](https://mlsanity.com/paper/1912.04958/) (2019)
- [Zero-Shot Learning Through Cross-Modal Transfer](https://mlsanity.com/paper/1301.3666/) (2013)
- [Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders](https://mlsanity.com/paper/1704.01279/) (2017)
- [Evaluation of CNN-based Automatic Music Tagging Models](https://mlsanity.com/paper/2006.00751/) (2020)
- [Crossing You in Style: Cross-modal Style Transfer from Music to Visual Arts](https://mlsanity.com/paper/2009.08083/) (2020)

## Built on by (most cited first, 11 of 11)

- [The Power of Sound (TPoS): Audio Reactive Video Generation with Stable Diffusion](https://mlsanity.com/paper/2309.04509/) (2023)
- [Sound-Guided Semantic Image Manipulation](https://mlsanity.com/paper/2112.00007/) (2021)
- [Sound-Guided Semantic Video Generation](https://mlsanity.com/paper/2204.09273/) (2022)
- [Audio-Sync Video Generation with Multi-Stream Temporal Control](https://mlsanity.com/paper/2506.08003/) (2025)
- [AVI-Edit: Audio-sync Video Instance Editing with Granularity-Aware Mask Refiner](https://mlsanity.com/paper/2512.10571/) (2025)
- [Robust Sound-Guided Image Manipulation](https://mlsanity.com/paper/2208.14114/) (2022)
- [Generating Realistic Images from In-the-wild Sounds](https://mlsanity.com/paper/2309.02405/) (2023)
- [Network Bending of Diffusion Models for Audio-Visual Generation](https://mlsanity.com/paper/2406.19589/) (2024)
- [Cross-modal Face- and Voice-style Transfer](https://mlsanity.com/paper/2302.13838/) (2023)
- [Robot Synesthesia: A Sound and Emotion Guided AI Painter](https://mlsanity.com/paper/2302.04850/) (2023)
- [LAV: Audio-Driven Dynamic Visual Generation with Neural Compression and StyleGAN2](https://mlsanity.com/paper/2505.10101/) (2025)

## Abstract (arXiv)

The goal of this paper to generate a visually appealing video that responds to music with a neural network so that each frame of the video reflects the musical characteristics of the corresponding audio clip. To achieve the goal, we propose a neural music visualizer directly mapping deep music embeddings to style embeddings of StyleGAN, named Tr"aumerAI, which consists of a music auto-tagging model using short-chunk CNN and StyleGAN2 pre-trained on WikiArt dataset. Rather than establishing an objective metric between musical and visual semantics, we manually labeled the pairs in a subjective manner. An annotator listened to 100 music clips of 10 seconds long and selected an image that suits the music among the 200 StyleGAN-generated examples. Based on the collected data, we trained a simple transfer function that converts an audio embedding to a style embedding. The generated examples show that the mapping between audio and video makes a certain level of intra-segment similarity and inter-segment dissimilarity.