mlsanityData to 14 Oct 2026

Mozualization: Crafting Music and Visual Representation with Multimodal AI

arXiv 2504.13891 ↗First posted 5 Apr 2025cs.HC cs.AIcited by 0

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Abstract (arXiv)

In this work, we introduce Mozualization, a music generation and editing tool that creates multi-style embedded music by integrating diverse inputs, such as keywords, images, and sound clips (e.g., segments from various pieces of music or even a playful cat's meow). Our work is inspired by the ways people express their emotions -- writing mood-descriptive poems or articles, creating drawings with warm or cool tones, or listening to sad or uplifting music. Building on this concept, we developed a tool that transforms these emotional expressions into a cohesive and expressive song, allowing users to seamlessly incorporate their unique preferences and inspirations. To evaluate the tool and, more importantly, gather insights for its improvement, we conducted a user study involving nine music enthusiasts. The study assessed user experience, engagement, and the impact of interacting with and listening to the generated music.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 7 of its 24 references that are in the map. First posted on arXiv 5 Apr 2025.

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7 of 24 references.

References · 7

  1. 2022BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generationcited by 4,322
  2. 2017MuseGAN: Multi-track Sequential Generative Adversarial Networks for Symbolic Music Generation and Accompanimentcited by 151
  3. 2017MidiNet: A Convolutional Generative Adversarial Network for Symbolic-domain Music Generationcited by 72
  4. 2017Deep Learning Techniques for Music Generation -- A Surveycited by 49
  5. 2023Video2Music: Suitable Music Generation from Videos using an Affective Multimodal Transformer modelcited by 37
  6. 2024MusicMagus: Zero-Shot Text-to-Music Editing via Diffusion Modelscited by 32
  7. 2024Seed-Music: A Unified Framework for High Quality and Controlled Music Generationcited by 22

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