activity
20192026
most citedMining Dual Emotion for Fake News Detection

245 citations · 456 across the 27 of their papers we have counts for

collaborators

32 papers

cs.SD2026

AnyEdit: A Unified Framework for Speech and Singing Voice Editing with Real-World Environmental Consistency

Yunjia Zhang, Junan Zhang, Jing Yang +3

We present AnyEdit, a unified, separation-free framework for speech and singing voice editing that preserves real-world acoustic environments, including noise, reverberation, and b…

cs.SD2026

Qwen-Music Technical Report

Jin Xu, Kangdi Wang, Ruibin Yuan +24

We introduce Qwen-Music, a music generation model that produces high-fidelity songs with complete vocals. It supports text-to-music generation from descriptions, lyrics, and musica…

cs.SD2026

MimicLM: Zero-Shot Voice Imitation through Autoregressive Modeling of Pseudo-Parallel Speech Corpora

Tao Feng, Yuxiang Wang, Yuancheng Wang +5

Voice imitation aims to transform source speech to match a reference speaker's timbre and speaking style while preserving linguistic content. A straightforward approach is to train…

cs.CL2026

Geometric Alignment without Functional Equivalence: A Layer-wise Analysis of the Speech-Text Modality Gap

Ming-Hao Hsu, Xueyao Zhang, Xiaohai Tian +4

End-to-end speech large language models (LLMs) often answer the same question less accurately from speech than from text, even when the spoken content matches the text prompt. Exis…

cs.SD2026

FlexiVoice: Enabling Flexible Style Control in Zero-Shot TTS with Natural Language Instructions

Dekun Chen, Xueyao Zhang, Yuancheng Wang +3

This study proposes FlexiVoice, a text-to-speech (TTS) synthesis system capable of flexible style control with zero-shot voice cloning. The speaking style is controlled by a natura…

cs.CL2026

Closing the Modality Reasoning Gap for Speech Large Language Models

Chaoren Wang, Heng Lu, Xueyao Zhang +4

Although Speech Large Language Models have achieved notable progress, a substantial modality reasoning gap remains: their reasoning performance on speech inputs is markedly weaker…

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

AnyAccomp: Generalizable Accompaniment Generation via Quantized Melodic Bottleneck

Junan Zhang, Yunjia Zhang, Xueyao Zhang +1

Singing Accompaniment Generation (SAG) is the process of generating instrumental music for a given clean vocal input. However, existing SAG techniques use source-separated vocals a…

eess.AS2025

Audio Deepfake Verification

Li Wang, Junyi Ao, Linyong Gan +3

With the rapid development of deepfake technology, simply making a binary judgment of true or false on audio is no longer sufficient to meet practical needs. Accurately determining…

cs.SD2025

An Extensive Analysis of the Singing Voice Conversion Challenge 2025 Evaluation Results

Lester Phillip Violeta, Xueyao Zhang, Jiatong Shi +4

We present a thorough analysis of the findings of the latest iteration of the Singing Voice Conversion Challenge, a scientific event aiming to compare and understand different voic…

cs.SD2025

TaDiCodec: Text-aware Diffusion Speech Tokenizer for Speech Language Modeling

Yuancheng Wang, Dekun Chen, Xueyao Zhang +3

Speech tokenizers serve as foundational components for speech language models, yet current designs exhibit several limitations, including: 1) dependence on multi-layer residual vec…

cs.SD2025

Multi-Metric Preference Alignment for Generative Speech Restoration

Junan Zhang, Xueyao Zhang, Jing Yang +3

Recent generative models have significantly advanced speech restoration tasks, yet their training objectives often misalign with human perceptual preferences, resulting in suboptim…

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.CL2025

From Judgment to Interference: Early Stopping LLM Harmful Outputs via Streaming Content Monitoring

Yang Li, Qiang Sheng, Yehan Yang +2

Though safety alignment has been applied to most large language models (LLMs), LLM service providers generally deploy a subsequent moderation as the external safety guardrail in re…

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

Vevo: Controllable Zero-Shot Voice Imitation with Self-Supervised Disentanglement

Xueyao Zhang, Xiaohui Zhang, Kainan Peng +10

The imitation of voice, targeted on specific speech attributes such as timbre and speaking style, is crucial in speech generation. However, existing methods rely heavily on annotat…

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

Metis: A Foundation Speech Generation Model with Masked Generative Pre-training

Yuancheng Wang, Jiachen Zheng, Junan Zhang +3

We introduce Metis, a foundation model for unified speech generation. Unlike previous task-specific or multi-task models, Metis follows a pre-training and fine-tuning paradigm. It…

cs.SD2024

Noro: Noise-Robust One-shot Voice Conversion with Hidden Speaker Representation Learning

Haorui He, Yuchen Song, Yuancheng Wang +6

The effectiveness of one-shot voice conversion (VC) decreases in real-world scenarios where reference speeches, which are often sourced from the internet, contain various disturban…

cs.SD2024

MaskGCT: Zero-Shot Text-to-Speech with Masked Generative Codec Transformer

Yuancheng Wang, Haoyue Zhan, Liwei Liu +7

The recent large-scale text-to-speech (TTS) systems are usually grouped as autoregressive and non-autoregressive systems. The autoregressive systems implicitly model duration but e…

cs.SD2024

An Investigation of Time-Frequency Representation Discriminators for High-Fidelity Vocoder

Yicheng Gu, Xueyao Zhang, Liumeng Xue +2

Generative Adversarial Network (GAN) based vocoders are superior in both inference speed and synthesis quality when reconstructing an audible waveform from an acoustic representati…

cs.SD2024★ 1 cited

SingVisio: Visual Analytics of Diffusion Model for Singing Voice Conversion

Liumeng Xue, Chaoren Wang, Mingxuan Wang +3

In this study, we present SingVisio, an interactive visual analysis system that aims to explain the diffusion model used in singing voice conversion. SingVisio provides a visual di…

cs.SD2023★ 3 cited

Amphion: An Open-Source Audio, Music and Speech Generation Toolkit

Xueyao Zhang, Liumeng Xue, Yicheng Gu +16

Amphion is an open-source toolkit for Audio, Music, and Speech Generation, targeting to ease the way for junior researchers and engineers into these fields. It presents a unified f…