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CLIPSonic: Text-to-Audio Synthesis with Unlabeled Videos and Pretrained Language-Vision Models
Our results show the effectiveness of the proposed method, and that the pretrained diffusion prior can reduce the modality transfer gap.
Full-band General Audio Synthesis with Score-based Diffusion
Recent works have shown the capability of deep generative models to tackle general audio synthesis from a single label, producing a variety of impulsive, tonal, and environmental sounds.
Adapting End-to-End Neural Speaker Verification to New Languages and Recording Conditions with Adversarial Training
In this article we propose a novel approach for adapting speaker embeddings to new domains based on adversarial training of neural networks.
Generative Adversarial Speaker Embedding Networks for Domain Robust End-to-End Speaker Verification
Furthermore, we are able to significantly boost verification performance by averaging our different GAN models at the score level, achieving a relative improvement of 7. 2% over the baseline.
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