activity
20242026
most citedSingMOS: An extensive Open-Source Singing Voice Dataset for MOS Prediction

3 citations · 3 across the 8 of their papers we have counts for

collaborators

9 papers

cs.SD2026

MMGenre: Benchmarking Singing Voice Synthesis across Multiple Musical Genres

Wenhao Feng, Yuxun Tang, Jiatong Shi +1

Singing voice synthesis (SVS) has progressed rapidly, yet its ability to generalize across diverse musical genres remains underexplored. Existing benchmarks are heavily biased towa…

cs.SD2025

SingMOS-Pro: An Comprehensive Benchmark for Singing Quality Assessment

Yuxun Tang, Lan Liu, Wenhao Feng +5

Singing voice generation progresses rapidly, yet evaluating singing quality remains a critical challenge. Human subjective assessment, typically in the form of listening tests, is…

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…

eess.AS2024

ESPnet-Codec: Comprehensive Training and Evaluation of Neural Codecs for Audio, Music, and Speech

Jiatong Shi, Jinchuan Tian, Yihan Wu +17

Neural codecs have become crucial to recent speech and audio generation research. In addition to signal compression capabilities, discrete codecs have also been found to enhance do…

cs.SD2024★ 3 cited

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

The Interspeech 2024 Challenge on Speech Processing Using Discrete Units

Xuankai Chang, Jiatong Shi, Jinchuan Tian +7

Representing speech and audio signals in discrete units has become a compelling alternative to traditional high-dimensional feature vectors. Numerous studies have highlighted the e…

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…