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20232026
most citedEmilia: A Large-Scale, Extensive, Multilingual, and Diverse Dataset for Speech Generation

8 citations · 14 across the 16 of their papers we have counts for

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10 papers · 1 filter

cs.SD2025

Aliasing-Free Neural Audio Synthesis

Yicheng Gu, Junan Zhang, Chaoren Wang +3

In neural audio synthesis, neural vocoders and codecs are models that reconstruct waveforms from acoustic and latent representations, which are essential to the resulting audio qua…

cs.SD2025

SpeechJudge: Towards Human-Level Judgment for Speech Naturalness

Xueyao Zhang, Chaoren Wang, Huan Liao +8

Aligning large generative models with human feedback is a critical challenge. In speech synthesis, this is particularly pronounced due to the lack of a large-scale human preference…

cs.SD2025

SP-MCQA: Evaluating Intelligibility of TTS Beyond the Word Level

Hitomi Jin Ling Tee, Chaoren Wang, Zijie Zhang +1

The evaluation of intelligibility for TTS has reached a bottleneck, as existing assessments heavily rely on word-by-word accuracy metrics such as WER, which fail to capture the com…

cs.SD2025

Vevo2: A Unified and Controllable Framework for Speech and Singing Voice Generation

Xueyao Zhang, Junan Zhang, Yuancheng Wang +5

Controllable human voice generation, particularly for expressive domains like singing, remains a significant challenge. This paper introduces Vevo2, a unified framework for control…

cs.SD2025

Advancing Zero-shot Text-to-Speech Intelligibility across Diverse Domains via Preference Alignment

Xueyao Zhang, Yuancheng Wang, Chaoren Wang +3

Modern zero-shot text-to-speech (TTS) systems, despite using extensive pre-training, often struggle in challenging scenarios such as tongue twisters, repeated words, code-switching…

cs.SD2025

SingNet: Towards a Large-Scale, Diverse, and In-the-Wild Singing Voice Dataset

Yicheng Gu, Chaoren Wang, Junan Zhang +4

The lack of a publicly-available large-scale and diverse dataset has long been a significant bottleneck for singing voice applications like Singing Voice Synthesis (SVS) and Singin…

cs.SD2025

Neurodyne: Neural Pitch Manipulation with Representation Learning and Cycle-Consistency GAN

Yicheng Gu, Chaoren Wang, Zhizheng Wu +1

Pitch manipulation is the process of producers adjusting the pitch of an audio segment to a specific key and intonation, which is essential in music production. Neural-network-base…

cs.SD2025

DualCodec: A Low-Frame-Rate, Semantically-Enhanced Neural Audio Codec for Speech Generation

Jiaqi Li, Xiaolong Lin, Zhekai Li +5

Neural audio codecs form the foundational building blocks for language model (LM)-based speech generation. Typically, there is a trade-off between frame rate and audio quality. Thi…

cs.SD2025

Overview of the Amphion Toolkit (v0.2)

Jiaqi Li, Xueyao Zhang, Yuancheng Wang +9

Amphion is an open-source toolkit for Audio, Music, and Speech Generation, designed to lower the entry barrier for junior researchers and engineers in these fields. It provides a v…

cs.SD2025★ 8 cited

Emilia: A Large-Scale, Extensive, Multilingual, and Diverse Dataset for Speech Generation

Haorui He, Zengqiang Shang, Chaoren Wang +11

Recent advancements in speech generation have been driven by large-scale training datasets. However, current models struggle to capture the spontaneity and variability inherent in…