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Open generative models are vitally important for the community, allowing for fine-tunes and serving as baselines when presenting new models. However, most current text-to-audio models are private and not accessible for artists and researchers to build upon. Here we describe the architecture and training process of a new open-weights text-to-audio model trained with Creative Commons data. Our evaluation shows that the model's performance is competitive with the state-of-the-art across various metrics. Notably, the reported FDopenl3 results (measuring the realism of the generations) showcase its potential for high-quality stereo sound synthesis at 44.1kHz.
Forward citations
Cited by 19 Pith papers
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Doppelganger: Sound Effects and Their Synthetic Twins
Instance-pair training matches synthetic sound-effect twins to their real sources on unseen events (~80% R@1), while class supervision degrades below the frozen baseline and the mapping stays generator-specific.
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On the Geometry of Music Bandwidth Extension in Latent Spaces of Audio Codecs
A single mean shift in the latent space of several neural codecs achieves competitive music bandwidth extension on some metrics, implying a largely linear structure.
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FlashDiff: Efficient Regional Execution and Scheduling for Diffusion Model Serving
FlashDiff reduces diffusion serving latency by 30–97% and raises throughput 1.2–2.2× by adaptively skipping refinement of latent regions that no longer need it.
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Qwen-Music Technical Report
Qwen-Music generates high-fidelity vocal songs via 25 Hz semantic tokens, Melody-CoT planning, and DiT rendering, claiming SOTA on 13/16 metrics and expert preference over proprietary systems.
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Unified Audio Intelligence Without Regressing on Text Intelligence
A unified 30B MoE audio-text LLM achieves state-of-the-art audio understanding, generation, and speech tasks while preserving text reasoning comparable to its text-only backbone.
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An Empirical Analysis of Task-Induced Encoder Bias in Fr\'echet Audio Distance
No single tested audio encoder catches all quality issues: reconstruction-trained encoders detect signal degradation, speech-trained encoders detect temporal order, and classification-trained encoders detect semantic ...
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SemanticAudio: Audio Generation and Editing in Semantic Space
SemanticAudio improves text-to-audio alignment by generating a compact semantic plan first with a Flow Matching planner and then rendering acoustic latents from that plan, and it performs training-free audio editing b...
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Amadeus: Autoregressive Model with Bidirectional Attribute Modelling for Symbolic Music
Amadeus generates symbolic music by autoregressively predicting note-level latents and decoding their attributes in parallel with a masked discrete diffusion model, yielding faster and more controllable generation tha...
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JAM: A Tiny Flow-based Song Generator with Fine-grained Controllability and Aesthetic Alignment
JAM is a 530M-parameter flow-matching song generator that adds word- and phoneme-level timing control and duration control, achieving strong lyric fidelity and musicality scores when ground-truth timings are provided.
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WildFX: A DAW-Powered Pipeline for In-the-Wild Audio FX Graph Modeling
WildFX generates multi-track audio datasets by rendering real DAW effect graphs with commercial plugins inside Docker, and demonstrates the pipeline on blind mixing-graph estimation.
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MusGO: A Community-Driven Framework For Assessing Openness in Music-Generative AI
MusGO is a community-refined framework with 13 openness categories, applied to 16 music-generative models to produce a public openness leaderboard.
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AI-Generated Song Detection via Lyrics Transcripts
Transcribing audio with Whisper and classifying the transcript with LLM2Vec detects AI-generated songs from audio alone, nearly matching clean-lyrics accuracy and beating audio-based detectors under perturbations and ...
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Video-Guided Text-to-Music Generation Using Public Domain Movie Collections
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.
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In-the-wild Audio Spatialization with Flexible Text-guided Localization
A text-guided latent diffusion model converts monaural audio into binaural audio whose perceived directions and distances follow user-specified text prompts.
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EgoZero: Robot Learning from Smart Glasses
Robot policies trained only on egocentric human videos from smart glasses transfer zero-shot to a Franka gripper, with 70% success across 7 manipulation tasks.
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RenderBox: Expressive Performance Rendering with Text Control
RenderBox is a text-and-score conditioned diffusion model that renders expressive, controllable audio performances across piano, guitar, saxophone, violin, and orchestral instruments.
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KVAE: Family of Tokenizers for Multimodal Generative Models
KVAE introduces image, video, and full-band audio tokenizers whose reconstruction and downstream generation quality is competitive with, and often better than, current open-source tokenizers in head-to-head tests.
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Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation
Boomerang sampling, applied to a pretrained music diffusion model, creates audio variations that improve beat tracking when training data is scarce and can change instruments via text prompts.
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SoloSpeech: Enhancing Intelligibility and Quality in Target Speech Extraction through a Cascaded Generative Pipeline
A cascaded pipeline of audio compression, latent diffusion extraction, and generative correction achieves state-of-the-art target speech extraction quality and intelligibility on Libri2Mix and out-of-domain data.
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