27 citations · 77 across the 19 of their papers we have counts for
19 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…
EmoSphere-TTS: Emotional Style and Intensity Modeling via Spherical Emotion Vector for Controllable Emotional Text-to-Speech
Deok-Hyeon Cho, Hyung-Seok Oh, Seung-Bin Kim +2
Despite rapid advances in the field of emotional text-to-speech (TTS), recent studies primarily focus on mimicking the average style of a particular emotion. As a result, the abili…
TranSentence: Speech-to-speech Translation via Language-agnostic Sentence-level Speech Encoding without Language-parallel Data
Seung-Bin Kim, Sang-Hoon Lee, Seong-Whan Lee
Although there has been significant advancement in the field of speech-to-speech translation, conventional models still require language-parallel speech data between the source and…
DurFlex-EVC: Duration-Flexible Emotional Voice Conversion Leveraging Discrete Representations without Text Alignment
Hyung-Seok Oh, Sang-Hoon Lee, Deok-Hyeon Cho +1
Emotional voice conversion (EVC) involves modifying various acoustic characteristics, such as pitch and spectral envelope, to match a desired emotional state while preserving the s…
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…
GC-TTS: Few-shot Speaker Adaptation with Geometric Constraints
Ji-Hoon Kim, Sang-Hoon Lee, Ji-Hyun Lee +2
Few-shot speaker adaptation is a specific Text-to-Speech (TTS) system that aims to reproduce a novel speaker's voice with a few training data. While numerous attempts have been mad…
Fre-GAN: Adversarial Frequency-consistent Audio Synthesis
Ji-Hoon Kim, Sang-Hoon Lee, Ji-Hyun Lee +1
Although recent works on neural vocoder have improved the quality of synthesized audio, there still exists a gap between generated and ground-truth audio in frequency space. This d…
Reinforce-Aligner: Reinforcement Alignment Search for Robust End-to-End Text-to-Speech
Hyunseung Chung, Sang-Hoon Lee, Seong-Whan Lee
Text-to-speech (TTS) synthesis is the process of producing synthesized speech from text or phoneme input. Traditional TTS models contain multiple processing steps and require exter…
Multi-SpectroGAN: High-Diversity and High-Fidelity Spectrogram Generation with Adversarial Style Combination for Speech Synthesis
Sang-Hoon Lee, Hyun-Wook Yoon, Hyeong-Rae Noh +2
While generative adversarial networks (GANs) based neural text-to-speech (TTS) systems have shown significant improvement in neural speech synthesis, there is no TTS system to lear…
Audio Dequantization for High Fidelity Audio Generation in Flow-based Neural Vocoder
Hyun-Wook Yoon, Sang-Hoon Lee, Hyeong-Rae Noh +1
In recent works, a flow-based neural vocoder has shown significant improvement in real-time speech generation task. The sequence of invertible flow operations allows the model to c…