1 citations · 2 across the 21 of their papers we have counts for
23 papers
UniVoice: A Unified Model for Speech and Singing Voice Generation
Junjie Zheng, Huixin Xue, Shihong Ren +3
Text-to-speech (TTS) and singing voice synthesis (SVS) both aim to generate human vocal audio from symbolic inputs, but they impose different requirements on the generation process…
YingMusic-SVC: Real-World Robust Zero-Shot Singing Voice Conversion with Flow-GRPO and Singing-Specific Inductive Biases
Gongyu Chen, Xiaoyu Zhang, Zhenqiang Weng +5
Singing voice conversion (SVC) aims to render the target singer's timbre while preserving melody and lyrics. However, existing zero-shot SVC systems remain fragile in real songs du…
YingMusic-Singer: Zero-shot Singing Voice Synthesis and Editing with Annotation-free Melody Guidance
Junjie Zheng, Chunbo Hao, Guobin Ma +5
Singing Voice Synthesis (SVS) remains constrained in practical deployment due to its strong dependence on accurate phoneme-level alignment and manually annotated melody contours, r…
YingVideo-MV: Music-Driven Multi-Stage Video Generation
Jiahui Chen, Weida Wang, Runhua Shi +3
While diffusion model for audio-driven avatar video generation have achieved notable process in synthesizing long sequences with natural audio-visual synchronization and identity c…
R2-SVC: Towards Real-World Robust and Expressive Zero-shot Singing Voice Conversion
Junjie Zheng, Gongyu Chen, Chaofan Ding +1
In real-world singing voice conversion (SVC) applications, environmental noise and the demand for expressive output pose significant challenges. Conventional methods, however, are…
DiaMoE-TTS: A Unified IPA-Based Dialect TTS Framework with Mixture-of-Experts and Parameter-Efficient Zero-Shot Adaptation
Ziqi Chen, Gongyu Chen, Yihua Wang +3
Dialect speech embodies rich cultural and linguistic diversity, yet building text-to-speech (TTS) systems for dialects remains challenging due to scarce data, inconsistent orthogra…
LD-LAudio-V1: Video-to-Long-Form-Audio Generation Extension with Dual Lightweight Adapters
Haomin Zhang, Kristin Qi, Shuxin Yang +3
Generating high-quality and temporally synchronized audio from video content is essential for video editing and post-production tasks, enabling the creation of semantically aligned…
DualDub: Video-to-Soundtrack Generation via Joint Speech and Background Audio Synthesis
Wenjie Tian, Xinfa Zhu, Haohe Liu +6
While recent video-to-audio (V2A) models can generate realistic background audio from visual input, they largely overlook speech, an essential part of many video soundtracks. This…
Towards Video to Piano Music Generation with Chain-of-Perform Support Benchmarks
Chang Liu, Haomin Zhang, Shiyu Xia +5
Generating high-quality piano audio from video requires precise synchronization between visual cues and musical output, ensuring accurate semantic and temporal alignment.However, e…
MM-MovieDubber: Towards Multi-Modal Learning for Multi-Modal Movie Dubbing
Junjie Zheng, Zihao Chen, Chaofan Ding +5
Current movie dubbing technology can produce the desired speech using a reference voice and input video, maintaining perfect synchronization with the visuals while effectively conv…
Towards Film-Making Production Dialogue, Narration, Monologue Adaptive Moving Dubbing Benchmarks
Chaoyi Wang, Junjie Zheng, Zihao Chen +6
Movie dubbing has advanced significantly, yet assessing the real-world effectiveness of these models remains challenging. A comprehensive evaluation benchmark is crucial for two ke…
DeepDubber-V1: Towards High Quality and Dialogue, Narration, Monologue Adaptive Movie Dubbing Via Multi-Modal Chain-of-Thoughts Reasoning Guidance
Junjie Zheng, Zihao Chen, Chaofan Ding +1
Current movie dubbing technology can generate the desired voice from a given speech prompt, ensuring good synchronization between speech and visuals while accurately conveying the…
DeepAudio-V1:Towards Multi-Modal Multi-Stage End-to-End Video to Speech and Audio Generation
Haomin Zhang, Chang Liu, Junjie Zheng +3
Currently, high-quality, synchronized audio is synthesized using various multi-modal joint learning frameworks, leveraging video and optional text inputs. In the video-to-audio ben…
DeepSound-V1: Start to Think Step-by-Step in the Audio Generation from Videos
Yunming Liang, Zihao Chen, Chaofan Ding +1
Currently, high-quality, synchronized audio is synthesized from video and optional text inputs using various multi-modal joint learning frameworks. However, the precise alignment b…
Enhance Generation Quality of Flow Matching V2A Model via Multi-Step CoT-Like Guidance and Combined Preference Optimization
Haomin Zhang, Sizhe Shan, Haoyu Wang +4
Creating high-quality sound effects from videos and text prompts requires precise alignment between visual and audio domains, both semantically and temporally, along with step-by-s…
Audio-driven Gesture Generation via Deviation Feature in the Latent Space
Jiahui Chen, Yang Huan, Runhua Shi +4
Gestures are essential for enhancing co-speech communication, offering visual emphasis and complementing verbal interactions. While prior work has concentrated on point-level motio…
Enhancing Reasoning through Process Supervision with Monte Carlo Tree Search
Shuangtao Li, Shuaihao Dong, Kexin Luan +2
Large language models (LLMs) have demonstrated their remarkable capacity across a variety of tasks. However, reasoning remains a challenge for LLMs. To improve LLMs' reasoning abil…
Towards Intrinsic Self-Correction Enhancement in Monte Carlo Tree Search Boosted Reasoning via Iterative Preference Learning
Huchen Jiang, Yangyang Ma, Chaofan Ding +2
With current state-of-the-art approaches aimed at enhancing the reasoning capabilities of Large Language Models(LLMs) through iterative preference learning inspired by AlphaZero, w…
Multiple Consistency-guided Test-Time Adaptation for Contrastive Audio-Language Models with Unlabeled Audio
Gongyu Chen, Haomin Zhang, Chaofan Ding +2
One fascinating aspect of pre-trained Audio-Language Models (ALMs) learning is their impressive zero-shot generalization capability and test-time adaptation (TTA) methods aiming to…
Low-Rank Adaptation with Task-Relevant Feature Enhancement for Fine-tuning Language Models
Changqun Li, Chaofan Ding, Kexin Luan +1
Fine-tuning pre-trained large language models in a parameter-efficient manner is widely studied for its effectiveness and efficiency. LoRA is one of the most widely used methods, w…
YingSound: Video-Guided Sound Effects Generation with Multi-modal Chain-of-Thought Controls
Zihao Chen, Haomin Zhang, Xinhan Di +10
Generating sound effects for product-level videos, where only a small amount of labeled data is available for diverse scenes, requires the production of high-quality sounds in few-…
Self-Supervised Learning of Deviation in Latent Representation for Co-speech Gesture Video Generation
Huan Yang, Jiahui Chen, Chaofan Ding +5
Gestures are pivotal in enhancing co-speech communication. While recent works have mostly focused on point-level motion transformation or fully supervised motion representations th…
Bailing-TTS: Chinese Dialectal Speech Synthesis Towards Human-like Spontaneous Representation
Xinhan Di, Zihao Chen, Yunming Liang +3
Large-scale text-to-speech (TTS) models have made significant progress recently.However, they still fall short in the generation of Chinese dialectal speech. Toaddress this, we pro…