3 citations · 5 across the 7 of their papers we have counts for
7 papers
ReGen: Hierarchical Multi-Prompt Representation Generation for Efficient Waveform Diffusion Models
Sang-Hoon Lee, Ha-Yeong Choi
Representation alignment (REPA) has been investigated to accelerate diffusion training, but we observe that regularizing intermediate representations in diffusion Transformers (DiT…
Accelerating High-Fidelity Waveform Generation via Adversarial Flow Matching Optimization
Sang-Hoon Lee, Ha-Yeong Choi, Seong-Whan Lee
This paper introduces PeriodWave-Turbo, a high-fidelity and high-efficient waveform generation model via adversarial flow matching optimization. Recently, conditional flow matching…
PeriodWave: Multi-Period Flow Matching for High-Fidelity Waveform Generation
Sang-Hoon Lee, Ha-Yeong Choi, Seong-Whan Lee
Recently, universal waveform generation tasks have been investigated conditioned on various out-of-distribution scenarios. Although GAN-based methods have shown their strength in f…
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.…
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…
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…