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Varianceflow: High-Quality and Controllable Text-to-Speech using Variance Information via Normalizing Flow

Varianceflow: High-Quality and Controllable Text-to-Speech using Variance Information via Normalizing Flow

Yoonhyung Lee
Jinhyeok Yang
Kyomin Jung
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Papers citing "Varianceflow: High-Quality and Controllable Text-to-Speech using Variance Information via Normalizing Flow"

5 / 5 papers shown
Title
FLOWER: Flow-Based Estimated Gaussian Guidance for General Speech Restoration
FLOWER: Flow-Based Estimated Gaussian Guidance for General Speech Restoration
Da-Hee Yang
Jaeuk Lee
Joon-Hyuk Chang
VLM
AI4CE
33
0
0
03 May 2025
An Exhaustive Evaluation of TTS- and VC-based Data Augmentation for ASR
Sewade Ogun
Vincent Colotte
Emmanuel Vincent
64
0
0
11 Mar 2025
MultiVerse: Efficient and Expressive Zero-Shot Multi-Task Text-to-Speech
MultiVerse: Efficient and Expressive Zero-Shot Multi-Task Text-to-Speech
Taejun Bak
Youngsik Eom
SeungJae Choi
Young-Sun Joo
29
0
0
04 Oct 2024
Stochastic Pitch Prediction Improves the Diversity and Naturalness of Speech in Glow-TTS
Stochastic Pitch Prediction Improves the Diversity and Naturalness of Speech in Glow-TTS
Sewade Ogun
Vincent Colotte
Emmanuel Vincent
DiffM
32
4
0
28 May 2023
PITS: Variational Pitch Inference without Fundamental Frequency for End-to-End Pitch-controllable TTS
PITS: Variational Pitch Inference without Fundamental Frequency for End-to-End Pitch-controllable TTS
Junhyeok Lee
Wonbin Jung
Hyunjae Cho
Jaeyeon Kim
Jaehwan Kim
17
3
0
24 Feb 2023