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Mo\^usai: Text-to-Music Generation with Long-Context Latent Diffusion

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arxiv 2301.11757 v3 pith:U6L7SYBO submitted 2023-01-27 cs.CL cs.LGcs.SDeess.AS

Flavio Schneider , Ojasv Kamal , Zhijing Jin , Bernhard Schölkopf This is my paper · ORCID
classification cs.CLcs.LGcs.SDeess.AS
keywords musicmodeltextgenerationmodelsopen-sourcediffusionhttps
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Recent years have seen the rapid development of large generative models for text; however, much less research has explored the connection between text and another "language" of communication -- music. Music, much like text, can convey emotions, stories, and ideas, and has its own unique structure and syntax. In our work, we bridge text and music via a text-to-music generation model that is highly efficient, expressive, and can handle long-term structure. Specifically, we develop Mo\^usai, a cascading two-stage latent diffusion model that can generate multiple minutes of high-quality stereo music at 48kHz from textual descriptions. Moreover, our model features high efficiency, which enables real-time inference on a single consumer GPU with a reasonable speed. Through experiments and property analyses, we show our model's competence over a variety of criteria compared with existing music generation models. Lastly, to promote the open-source culture, we provide a collection of open-source libraries with the hope of facilitating future work in the field. We open-source the following: Codes: https://github.com/archinetai/audio-diffusion-pytorch; music samples for this paper: http://bit.ly/44ozWDH; all music samples for all models: https://bit.ly/audio-diffusion.

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Forward citations

Cited by 10 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Diff-Symbo: Text-Controlled Long-Duration Symbolic Music Generation Using Autoregressive Latent Diffusion Model

    cs.SD 2026-08 conditional novelty 6.0 of 10

    Diff-Symbo generates long, text-controlled symbolic music by autoregressively extending 8-bar latent diffusion segments conditioned on the previous segment's latent.

  2. Dance to Music Generation leveraging Pre-training with Unpaired data and Contrastive Alignment

    cs.SD 2026-07 conditional novelty 6.0 of 10

    Beat-guided contrastive alignment of pretrained MotionBERT/MERT features plus ControlNet conditioning of AudioLDM improves dance–music alignment on AIST++ over a MusicGen textual-inversion baseline while remaining com...

  3. Next Tokens Denoising for Speech Synthesis

    cs.SD 2025-07 conditional novelty 6.0 of 10

    Dragon-FM generates speech autoregressively over two-second chunks while using flow matching inside each chunk, achieving fast synthesis at 12.5 discrete audio tokens per second.

  4. MusGO: A Community-Driven Framework For Assessing Openness in Music-Generative AI

    cs.SD 2025-07 conditional novelty 6.0 of 10

    MusGO is a community-refined framework with 13 openness categories, applied to 16 music-generative models to produce a public openness leaderboard.

  5. Video-Guided Text-to-Music Generation Using Public Domain Movie Collections

    cs.SD 2025-06 conditional novelty 6.0 of 10

    OSSL is the first self-hosted, mood-annotated video-music dataset, and a video adapter on MusicGen-Medium improves film music generation over text-only baselines.

  6. A Mixture-Based Framework for Guiding Diffusion Models

    stat.ML 2025-02 conditional novelty 6.0 of 10

    MGDM approximates the intractable guided-diffusion posterior with a weighted mixture of likelihood approximations and samples the mixture using a Gibbs sampler with tunable repetitions.

  7. CoDiCodec: Unifying Continuous and Discrete Compressed Representations of Audio

    cs.SD 2025-09 conditional novelty 5.0 of 10

    CoDiCodec unifies continuous and discrete audio compression in one consistency-trained autoencoder, using FSQ-dropout to serve both continuous ~11 Hz embeddings and 2.38 kbps discrete tokens.

  8. Workflow-Based Evaluation of Music Generation Systems

    eess.AS 2025-06 conditional novelty 5.0 of 10

    A single-producer workflow evaluation of eight music AI tools finds they work as idea and sound generators but not as complete composers, and proposes a reusable framework.

  9. FlowSonic: Stable Zero-Shot Music Editing via High-Order Trajectory Integration

    cs.SD 2026-07 reject novelty 4.0 of 10

    FlowSonic combines deterministic rectified-flow inversion, cached cross-attention injection, and a 'seeded' third-order Adams-Bashforth solver to report better timbre and genre edits on small datasets.

  10. ASAudio: A Survey of Advanced Spatial Audio Research

    eess.AS 2025-08 unverdicted novelty 3.0 of 10

    A comprehensive survey that systematically categorizes spatial audio research by representation, task, dataset, and evaluation.

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