11 papers · 1 filter
EDNet: A Versatile Speech Enhancement Framework with Gating Mamba Mechanism and Phase Shift-Invariant Training
Doyeop Kwak, Youngjoon Jang, Seongyu Kim +1
Speech signals in real-world environments are frequently affected by various distortions such as additive noise, reverberation, and bandwidth limitation, which may appear individua…
LP-CFM: Perceptual Invariance-Aware Conditional Flow Matching for Speech Modeling
Doyeop Kwak, Youngjoon Jang, Joon Son Chung
The goal of this paper is to provide a new perspective on speech modeling by incorporating perceptual invariances such as amplitude scaling and temporal shifts. Conventional genera…
InfiniteAudio: Infinite-Length Audio Generation with Consistency
Chaeyoung Jung, Hojoon Ki, Ji-Hoon Kim +2
This paper presents InfiniteAudio, a simple yet effective strategy for generating infinite-length audio using diffusion-based text-to-audio methods. Current approaches face memory…
Text-To-Speech Synthesis In The Wild
Jee-weon Jung, Wangyou Zhang, Soumi Maiti +11
Traditional Text-to-Speech (TTS) systems rely on studio-quality speech recorded in controlled settings.a Recently, an effort known as noisy-TTS training has emerged, aiming to util…
Accelerating Diffusion-based Text-to-Speech Model Training with Dual Modality Alignment
Jeongsoo Choi, Zhikang Niu, Ji-Hoon Kim +3
The goal of this paper is to optimize the training process of diffusion-based text-to-speech models. While recent studies have achieved remarkable advancements, their training dema…
From Faces to Voices: Learning Hierarchical Representations for High-quality Video-to-Speech
Ji-Hoon Kim, Jeongsoo Choi, Jaehun Kim +2
The objective of this study is to generate high-quality speech from silent talking face videos, a task also known as video-to-speech synthesis. A significant challenge in video-to-…