62 citations · 105 across the 10 of their papers we have counts for
10 papers
DRAFT: Dense Retrieval Augmented Few-shot Topic classifier Framework
Keonwoo Kim, Younggun Lee
With the growing volume of diverse information, the demand for classifying arbitrary topics has become increasingly critical. To address this challenge, we introduce DRAFT, a simpl…
RobustSwap: A Simple yet Robust Face Swapping Model against Attribute Leakage
Jaeseong Lee, Taewoo Kim, Sunghyun Park +2
Face swapping aims at injecting a source image's identity (i.e., facial features) into a target image, while strictly preserving the target's attributes, which are irrelevant to id…
Cross-speaker Emotion Transfer by Manipulating Speech Style Latents
Suhee Jo, Younggun Lee, Yookyung Shin +2
In recent years, emotional text-to-speech has shown considerable progress. However, it requires a large amount of labeled data, which is not easily accessible. Even if it is possib…
Text-driven Emotional Style Control and Cross-speaker Style Transfer in Neural TTS
Yookyung Shin, Younggun Lee, Suhee Jo +2
Expressive text-to-speech has shown improved performance in recent years. However, the style control of synthetic speech is often restricted to discrete emotion categories and requ…
MLP Singer: Towards Rapid Parallel Korean Singing Voice Synthesis
Jaesung Tae, Hyeongju Kim, Younggun Lee
Recent developments in deep learning have significantly improved the quality of synthesized singing voice audio. However, prominent neural singing voice synthesis systems suffer fr…
Large-scale Speaker Retrieval on Random Speaker Variability Subspace
Suwon Shon, Younggun Lee, Taesu Kim
This paper describes a fast speaker search system to retrieve segments of the same voice identity in the large-scale data. A recent study shows that Locality Sensitive Hashing (LSH…
Learning pronunciation from a foreign language in speech synthesis networks
Younggun Lee, Suwon Shon, Taesu Kim
Although there are more than 6,500 languages in the world, the pronunciations of many phonemes sound similar across the languages. When people learn a foreign language, their pronu…
Robust and fine-grained prosody control of end-to-end speech synthesis
Younggun Lee, Taesu Kim
We propose prosody embeddings for emotional and expressive speech synthesis networks. The proposed methods introduce temporal structures in the embedding networks, thus enabling fi…
Voice Imitating Text-to-Speech Neural Networks
Younggun Lee, Taesu Kim, Soo-Young Lee
We propose a neural text-to-speech (TTS) model that can imitate a new speaker's voice using only a small amount of speech sample. We demonstrate voice imitation using only a 6-seco…
Emotional End-to-End Neural Speech Synthesizer
Younggun Lee, Azam Rabiee, Soo-Young Lee
In this paper, we introduce an emotional speech synthesizer based on the recent end-to-end neural model, named Tacotron. Despite its benefits, we found that the original Tacotron s…