4 papers · 1 filter
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…
MAGE: A Coarse-to-Fine Speech Enhancer with Masked Generative Model
The Hieu Pham, Tan Dat Nguyen, Phuong Thanh Tran +2
Speech enhancement remains challenging due to the trade-off between efficiency and perceptual quality. In this paper, we introduce MAGE, a Masked Audio Generative Enhancer that adv…
VoiceDiT: Dual-Condition Diffusion Transformer for Environment-Aware Speech Synthesis
Jaemin Jung, Junseok Ahn, Chaeyoung Jung +3
We present VoiceDiT, a multi-modal generative model for producing environment-aware speech and audio from text and visual prompts. While aligning speech with text is crucial for in…
Wanna hear your voice? A sample is all we need!
The Hieu Pham, Phuong Thanh Tran Nguyen, Xuan Tho Nguyen +2
Research on audio clue-based target speaker extraction (TSE) has focused on modeling mixtures and reference speech, achieving strong results in English due to abundant datasets. Ho…