3 citations · 4 across the 11 of their papers we have counts for
11 papers
AudioX-Turbo: A Unified Framework for Efficient Anything-to-Audio Generation
Zeyue Tian, Lei Ke, Zhaoyang Liu +8
Audio and music generation based on flexible multimodal control signals is a widely applicable topic, with the following key challenges: 1) a unified multimodal modeling framework,…
Which Speech Representation Better Matches Text-Native Reasoning? A Study of Speech-Text Alignment on Frame Rate and Representation
Zhen Ye, Xu Tan, Yiming Li +10
Spoken dialogue models typically start from text LLM backbones, yet reasoning often degrades when conditioning on speech instead of text. We attribute part of this modality gap to…
Talker-T2AV: Joint Talking Audio-Video Generation with Autoregressive Diffusion Modeling
Zhen Ye, Xu Tan, Aoxiong Yin +8
Joint audio-video generation models have shown that unified generation yields stronger cross-modal coherence than cascaded approaches. However, existing models couple modalities th…
AudioX: A Unified Framework for Anything-to-Audio Generation
Zeyue Tian, Zhaoyang Liu, Yizhu Jin +6
Audio and music generation based on flexible multimodal control signals is a widely applicable topic, with the following key challenges: 1) a unified multimodal modeling framework,…
Llasa: Scaling Train-Time and Inference-Time Compute for Llama-based Speech Synthesis
Zhen Ye, Xinfa Zhu, Chi-Min Chan +17
Recent advances in text-based large language models (LLMs), particularly in the GPT series and the o1 model, have demonstrated the effectiveness of scaling both training-time and i…
Codec Does Matter: Exploring the Semantic Shortcoming of Codec for Audio Language Model
Zhen Ye, Peiwen Sun, Jiahe Lei +9
Recent advancements in audio generation have been significantly propelled by the capabilities of Large Language Models (LLMs). The existing research on audio LLM has primarily focu…
VidMuse: A Simple Video-to-Music Generation Framework with Long-Short-Term Modeling
Zeyue Tian, Zhaoyang Liu, Ruibin Yuan +6
In this work, we systematically study music generation conditioned solely on the video. First, we present a large-scale dataset comprising 360K video-music pairs, including various…
FastSAG: Towards Fast Non-Autoregressive Singing Accompaniment Generation
Jianyi Chen, Wei Xue, Xu Tan +3
Singing Accompaniment Generation (SAG), which generates instrumental music to accompany input vocals, is crucial to developing human-AI symbiotic art creation systems. The state-of…
FlashSpeech: Efficient Zero-Shot Speech Synthesis
Zhen Ye, Zeqian Ju, Haohe Liu +10
Recent progress in large-scale zero-shot speech synthesis has been significantly advanced by language models and diffusion models. However, the generation process of both methods i…
MuPT: A Generative Symbolic Music Pretrained Transformer
Xingwei Qu, Yuelin Bai, Yinghao Ma +25
In this paper, we explore the application of Large Language Models (LLMs) to the pre-training of music. While the prevalent use of MIDI in music modeling is well-established, our f…
CoMoSVC: Consistency Model-based Singing Voice Conversion
Yiwen Lu, Zhen Ye, Wei Xue +3
The diffusion-based Singing Voice Conversion (SVC) methods have achieved remarkable performances, producing natural audios with high similarity to the target timbre. However, the i…