4 papers
TextReg: Mitigating Prompt Distributional Overfitting via Regularized Text-Space Optimization
Lucheng Fu, Ye Yu, Yiyang Wang +4
Large language models (LLMs) are highly sensitive to the prompts used to specify task objectives and behavioral constraints. Many recent prompt optimization methods iteratively rew…
RobustSpeechFlow: Learning Robust Text-to-Speech Trajectories via Augmentation-based Contrastive Flow Matching
Jinhyeok Yang, Hyeongju Kim, Yechan Yu +3
While flow-matching text-to-speech (TTS) achieves strong zero-shot speaker similarity and naturalness, it remains susceptible to content fidelity issues, particularly skip and repe…
Training Flow Matching Models with Reliable Labels via Self-Purification
Hyeongju Kim, Yechan Yu, June Young Yi +1
Training datasets are inherently imperfect, often containing mislabeled samples due to human annotation errors, limitations of tagging models, and other sources of noise. Such labe…
SupertonicTTS: Towards Highly Efficient and Streamlined Text-to-Speech System
Hyeongju Kim, Jinhyeok Yang, Yechan Yu +5
We introduce SupertonicTTS, a novel text-to-speech (TTS) system designed for efficient and streamlined speech synthesis. SupertonicTTS comprises three components: a speech autoenco…