FlexiSLM is the first spoken language model supporting dynamic and controllable frame rates on speech input and output, outperforming fixed-rate 7B models at high quality and enabling faster inference at lower rates like 6.25 Hz.
Vampnet: Music generation via masked acous- tic token modeling
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LatentFT uses latent-space Fourier transforms and frequency masking in diffusion autoencoders to enable timescale-specific manipulation of musical structure in generative models.
The paper introduces target-KL regularization to train audio VAEs at specific bitrates, enabling rate-distortion curves and comparison to discrete audio codecs for improved text-to-sound generation.
LaDA-Band generates complete vocal-aligned instrumental accompaniments with discrete masked diffusion, claiming simultaneous gains in audio fidelity, long-range coherence, and orchestration quality.
citing papers explorer
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FlexiSLM: A Dynamic and Controllable Frame Rate Spoken Language Model
FlexiSLM is the first spoken language model supporting dynamic and controllable frame rates on speech input and output, outperforming fixed-rate 7B models at high quality and enabling faster inference at lower rates like 6.25 Hz.
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Latent Fourier Transform
LatentFT uses latent-space Fourier transforms and frequency masking in diffusion autoencoders to enable timescale-specific manipulation of musical structure in generative models.
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Taming Audio VAEs via Target-KL Regularization
The paper introduces target-KL regularization to train audio VAEs at specific bitrates, enabling rate-distortion curves and comparison to discrete audio codecs for improved text-to-sound generation.
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LaDA-Band: Language Diffusion Models for Vocal-to-Accompaniment Generation
LaDA-Band generates complete vocal-aligned instrumental accompaniments with discrete masked diffusion, claiming simultaneous gains in audio fidelity, long-range coherence, and orchestration quality.