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20242026
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cs.SD2024

VISinger2+: End-to-End Singing Voice Synthesis Augmented by Self-Supervised Learning Representation

Yifeng Yu, Jiatong Shi, Yuning Wu +2

Singing Voice Synthesis (SVS) has witnessed significant advancements with the advent of deep learning techniques. However, a significant challenge in SVS is the scarcity of labeled…

cs.SD2024

Muskits-ESPnet: A Comprehensive Toolkit for Singing Voice Synthesis in New Paradigm

Yuning Wu, Jiatong Shi, Yifeng Yu +7

This research presents Muskits-ESPnet, a versatile toolkit that introduces new paradigms to Singing Voice Synthesis (SVS) through the application of pretrained audio models in both…

cs.SD2024

SingMOS: An extensive Open-Source Singing Voice Dataset for MOS Prediction

Yuxun Tang, Jiatong Shi, Yuning Wu +1

In speech generation tasks, human subjective ratings, usually referred to as the opinion score, are considered the "gold standard" for speech quality evaluation, with the mean opin…

cs.SD2024

SingOMD: Singing Oriented Multi-resolution Discrete Representation Construction from Speech Models

Yuxun Tang, Yuning Wu, Jiatong Shi +1

Discrete representation has shown advantages in speech generation tasks, wherein discrete tokens are derived by discretizing hidden features from self-supervised learning (SSL) pre…

cs.SD2024

TokSing: Singing Voice Synthesis based on Discrete Tokens

Yuning Wu, Chunlei zhang, Jiatong Shi +3

Recent advancements in speech synthesis witness significant benefits by leveraging discrete tokens extracted from self-supervised learning (SSL) models. Discrete tokens offer highe…

cs.SD2024

Singing Voice Data Scaling-up: An Introduction to ACE-Opencpop and ACE-KiSing

Jiatong Shi, Yueqian Lin, Xinyi Bai +6

In singing voice synthesis (SVS), generating singing voices from musical scores faces challenges due to limited data availability. This study proposes a unique strategy to address…