50 citations · 51 across the 7 of their papers we have counts for
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DualSpeech: Enhancing Speaker-Fidelity and Text-Intelligibility Through Dual Classifier-Free Guidance
Jinhyeok Yang, Junhyeok Lee, Hyeong-Seok Choi +3
Text-to-Speech (TTS) models have advanced significantly, aiming to accurately replicate human speech's diversity, including unique speaker identities and linguistic nuances. Despit…
JenGAN: Stacked Shifted Filters in GAN-Based Speech Synthesis
Hyunjae Cho, Junhyeok Lee, Wonbin Jung
Non-autoregressive GAN-based neural vocoders are widely used due to their fast inference speed and high perceptual quality. However, they often suffer from audible artifacts such a…
Diversifying and Expanding Frequency-Adaptive Convolution Kernels for Sound Event Detection
Hyeonuk Nam, Seong-Hu Kim, Deokki Min +2
Frequency dynamic convolution (FDY conv) has shown the state-of-the-art performance in sound event detection (SED) using frequency-adaptive kernels obtained by frequency-varying co…
VIFS: An End-to-End Variational Inference for Foley Sound Synthesis
Junhyeok Lee, Hyeonuk Nam, Yong-Hwa Park
The goal of DCASE 2023 Challenge Task 7 is to generate various sound clips for Foley sound synthesis (FSS) by "category-to-sound" approach. "Category" is expressed by a single inde…
PITS: Variational Pitch Inference without Fundamental Frequency for End-to-End Pitch-controllable TTS
Junhyeok Lee, Wonbin Jung, Hyunjae Cho +2
Previous pitch-controllable text-to-speech (TTS) models rely on directly modeling fundamental frequency, leading to low variance in synthesized speech. To address this issue, we pr…
NU-Wave 2: A General Neural Audio Upsampling Model for Various Sampling Rates
Seungu Han, Junhyeok Lee
Conventionally, audio super-resolution models fixed the initial and the target sampling rates, which necessitate the model to be trained for each pair of sampling rates. We introdu…