9 papers
LRS-VoxMM: A benchmark for in-the-wild audio-visual speech recognition
Doyeop Kwak, Jeongsoo Choi, Suyeon Lee +1
We introduce LRS-VoxMM, an in-the-wild benchmark for audio-visual speech recognition (AVSR). The benchmark is derived from VoxMM, a dataset of diverse real-world spoken conversatio…
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…
Dub-S2ST: Textless Speech-to-Speech Translation for Seamless Dubbing
Jeongsoo Choi, Jaehun Kim, Joon Son Chung
This paper introduces a cross-lingual dubbing system that translates speech from one language to another while preserving key characteristics such as duration, speaker identity, an…
VoiceCraft-Dub: Automated Video Dubbing with Neural Codec Language Models
Kim Sung-Bin, Jeongsoo Choi, Puyuan Peng +3
We present VoiceCraft-Dub, a novel approach for automated video dubbing that synthesizes high-quality speech from text and facial cues. This task has broad applications in filmmaki…
AlignDiT: Multimodal Aligned Diffusion Transformer for Synchronized Speech Generation
Jeongsoo Choi, Ji-Hoon Kim, Kim Sung-Bin +2
In this paper, we address the task of multimodal-to-speech generation, which aims to synthesize high-quality speech from multiple input modalities: text, video, and reference audio…
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-…