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Found 5 papers, 3 papers with code
PodAgent: A Comprehensive Framework for Podcast Generation
The key challenges lie in in-depth content generation, appropriate and expressive voice production.
Audio-FLAN: A Preliminary Release
Audio-FLAN lays the foundation for unified audio-language models that can seamlessly handle both understanding (e. g., transcription, comprehension) and generation (e. g., speech, music, sound) tasks across a wide range of audio domains in a zero-shot manner.
ZSVC: Zero-shot Style Voice Conversion with Disentangled Latent Diffusion Models and Adversarial Training
Style voice conversion aims to transform the speaking style of source speech into a desired style while keeping the original speaker's identity.
QS-TTS: Towards Semi-Supervised Text-to-Speech Synthesis via Vector-Quantized Self-Supervised Speech Representation Learning
This paper proposes a novel semi-supervised TTS framework, QS-TTS, to improve TTS quality with lower supervised data requirements via Vector-Quantized Self-Supervised Speech Representation Learning (VQ-S3RL) utilizing more unlabeled speech audio.
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