1 citations · 2 across the 27 of their papers we have counts for
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CrossSpeech++: Cross-lingual Speech Synthesis with Decoupled Language and Speaker Generation
Ji-Hoon Kim, Hong-Sun Yang, Yoon-Cheol Ju +3
The goal of this work is to generate natural speech in multiple languages while maintaining the same speaker identity, a task known as cross-lingual speech synthesis. A key challen…
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…
V2SFlow: Video-to-Speech Generation with Speech Decomposition and Rectified Flow
Jeongsoo Choi, Ji-Hoon Kim, Jinyu Li +2
In this paper, we introduce V2SFlow, a novel Video-to-Speech (V2S) framework designed to generate natural and intelligible speech directly from silent talking face videos. While re…
Accelerating Codec-based Speech Synthesis with Multi-Token Prediction and Speculative Decoding
Tan Dat Nguyen, Ji-Hoon Kim, Jeongsoo Choi +4
The goal of this paper is to accelerate codec-based speech synthesis systems with minimum sacrifice to speech quality. We propose an enhanced inference method that allows for flexi…
Let Me Finish My Sentence: Video Temporal Grounding with Holistic Text Understanding
Jongbhin Woo, Hyeonggon Ryu, Youngjoon Jang +2
Video Temporal Grounding (VTG) aims to identify visual frames in a video clip that match text queries. Recent studies in VTG employ cross-attention to correlate visual frames and t…
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…
Bridging the Gap between Audio and Text using Parallel-attention for User-defined Keyword Spotting
Youkyum Kim, Jaemin Jung, Jihwan Park +2
This paper proposes a novel user-defined keyword spotting framework that accurately detects audio keywords based on text enrollment. Since audio data possesses additional acoustic…
VoxSim: A perceptual voice similarity dataset
Junseok Ahn, Youkyum Kim, Yeunju Choi +4
This paper introduces VoxSim, a dataset of perceptual voice similarity ratings. Recent efforts to automate the assessment of speech synthesis technologies have primarily focused on…
FlowAVSE: Efficient Audio-Visual Speech Enhancement with Conditional Flow Matching
Chaeyoung Jung, Suyeon Lee, Ji-Hoon Kim +1
This work proposes an efficient method to enhance the quality of corrupted speech signals by leveraging both acoustic and visual cues. While existing diffusion-based approaches hav…
Faces that Speak: Jointly Synthesising Talking Face and Speech from Text
Youngjoon Jang, Ji-Hoon Kim, Junseok Ahn +6
The goal of this work is to simultaneously generate natural talking faces and speech outputs from text. We achieve this by integrating Talking Face Generation (TFG) and Text-to-Spe…
FreGrad: Lightweight and Fast Frequency-aware Diffusion Vocoder
Tan Dat Nguyen, Ji-Hoon Kim, Youngjoon Jang +2
The goal of this paper is to generate realistic audio with a lightweight and fast diffusion-based vocoder, named FreGrad. Our framework consists of the following three key componen…