3 papers
eess.AS2025
SPADE: Structured Pruning and Adaptive Distillation for Efficient LLM-TTS
Tan Dat Nguyen, Jaehun Kim, Ji-Hoon Kim +3
The goal of this paper is to introduce SPADE, a framework for Structured Pruning and Adaptive Distillation for Efficient Large Language Model-based text-to-speech (LLM-TTS). Recent…
cs.CV2023
That's What I Said: Fully-Controllable Talking Face Generation
Youngjoon Jang, Kyeongha Rho, Jong-Bin Woo +5
The goal of this paper is to synthesise talking faces with controllable facial motions. To achieve this goal, we propose two key ideas. The first is to establish a canonical space…
eess.AS2022
Metric Learning for User-defined Keyword Spotting
Jaemin Jung, Youkyum Kim, Jihwan Park +4
The goal of this work is to detect new spoken terms defined by users. While most previous works address Keyword Spotting (KWS) as a closed-set classification problem, this limits t…