27 citations · 77 across the 19 of their papers we have counts for
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HierSpeech++: Bridging the Gap between Semantic and Acoustic Representation of Speech by Hierarchical Variational Inference for Zero-shot Speech Synthesis
Sang-Hoon Lee, Ha-Yeong Choi, Seung-Bin Kim +1
Large language models (LLM)-based speech synthesis has been widely adopted in zero-shot speech synthesis. However, they require a large-scale data and possess the same limitations…
Diff-HierVC: Diffusion-based Hierarchical Voice Conversion with Robust Pitch Generation and Masked Prior for Zero-shot Speaker Adaptation
Ha-Yeong Choi, Sang-Hoon Lee, Seong-Whan Lee
Although voice conversion (VC) systems have shown a remarkable ability to transfer voice style, existing methods still have an inaccurate pitch and low speaker adaptation quality.…
DiffProsody: Diffusion-based Latent Prosody Generation for Expressive Speech Synthesis with Prosody Conditional Adversarial Training
Hyung-Seok Oh, Sang-Hoon Lee, Seong-Whan Lee
Expressive text-to-speech systems have undergone significant advancements owing to prosody modeling, but conventional methods can still be improved. Traditional approaches have rel…
HierVST: Hierarchical Adaptive Zero-shot Voice Style Transfer
Sang-Hoon Lee, Ha-Yeong Choi, Hyung-Seok Oh +1
Despite rapid progress in the voice style transfer (VST) field, recent zero-shot VST systems still lack the ability to transfer the voice style of a novel speaker. In this paper, w…
PauseSpeech: Natural Speech Synthesis via Pre-trained Language Model and Pause-based Prosody Modeling
Ji-Sang Hwang, Sang-Hoon Lee, Seong-Whan Lee
Although text-to-speech (TTS) systems have significantly improved, most TTS systems still have limitations in synthesizing speech with appropriate phrasing. For natural speech synt…
HiddenSinger: High-Quality Singing Voice Synthesis via Neural Audio Codec and Latent Diffusion Models
Ji-Sang Hwang, Sang-Hoon Lee, Seong-Whan Lee
Recently, denoising diffusion models have demonstrated remarkable performance among generative models in various domains. However, in the speech domain, the application of diffusio…
DDDM-VC: Decoupled Denoising Diffusion Models with Disentangled Representation and Prior Mixup for Verified Robust Voice Conversion
Ha-Yeong Choi, Sang-Hoon Lee, Seong-Whan Lee
Diffusion-based generative models have exhibited powerful generative performance in recent years. However, as many attributes exist in the data distribution and owing to several li…
Task-Adaptive Pseudo Labeling for Transductive Meta-Learning
Sanghyuk Lee, Seunghyun Lee, Byung Cheol Song
Meta-learning performs adaptation through a limited amount of support set, which may cause a sample bias problem. To solve this problem, transductive meta-learning is getting more…