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20242026
most citedText-To-Speech Synthesis In The Wild

1 citations · 1 across the 22 of their papers we have counts for

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eess.AS2024

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…

cs.CV2024

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…

cs.SD2024

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…

cs.SD2024

SpoofCeleb: Speech Deepfake Detection and SASV In The Wild

Jee-weon Jung, Yihan Wu, Xin Wang +11

This paper introduces SpoofCeleb, a dataset designed for Speech Deepfake Detection (SDD) and Spoofing-robust Automatic Speaker Verification (SASV), utilizing source data from real-…

eess.AS2024★ 1 cited

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…

eess.AS2024

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…

eess.AS2024

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…

cs.CV2024

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…

eess.AS2024

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…