2 citations · 2 across the 11 of their papers we have counts for
11 papers
UniSRM: A Unified Speech Reward Model for Reasoning-Based Fine-grained Assessment
Yuanyuan Wang, Dongchao Yang, Yayue Deng +4
Evaluating speech generation still relies heavily on human judgments, such as Mean Opinion Score (MOS), which are expensive, subjective, and difficult to reproduce at scale. While…
UniAudio 2.0: A Unified Audio Language Model with Text-Aligned Factorized Audio Tokenization
Dongchao Yang, Yuanyuan Wang, Dading Chong +3
We study two foundational problems in audio language models: (1) how to design an audio tokenizer that can serve as an intermediate representation for both understanding and genera…
HeartMuLa: A Family of Open Sourced Music Foundation Models
Dongchao Yang, Yuxin Xie, Yuguo Yin +26
We present a family of open-source Music Foundation Models designed to advance large-scale music understanding and generation across diverse tasks and modalities. Our framework con…
Omni-AutoThink: Adaptive Multimodal Reasoning via Reinforcement Learning
Dongchao Yang, Songxiang Liu, Disong Wang +3
Recent advances in Omni models have enabled unified multimodal perception and generation. However, most existing systems still exhibit rigid reasoning behaviors, either overthinkin…
DualSpeechLM: Towards Unified Speech Understanding and Generation via Dual Speech Token Modeling with Large Language Models
Yuanyuan Wang, Dongchao Yang, Yiwen Shao +5
Extending pre-trained text Large Language Models (LLMs)'s speech understanding or generation abilities by introducing various effective speech tokens has attracted great attention…
ALMTokenizer: A Low-bitrate and Semantic-rich Audio Codec Tokenizer for Audio Language Modeling
Dongchao Yang, Songxiang Liu, Haohan Guo +9
Recent advancements in audio language models have underscored the pivotal role of audio tokenization, which converts audio signals into discrete tokens, thereby facilitating the ap…
UniSep: Universal Target Audio Separation with Language Models at Scale
Yuanyuan Wang, Hangting Chen, Dongchao Yang +7
We propose Universal target audio Separation (UniSep), addressing the separation task on arbitrary mixtures of different types of audio. Distinguished from previous studies, UniSep…
AudioComposer: Towards Fine-grained Audio Generation with Natural Language Descriptions
Yuanyuan Wang, Hangting Chen, Dongchao Yang +2
Current Text-to-audio (TTA) models mainly use coarse text descriptions as inputs to generate audio, which hinders models from generating audio with fine-grained control of content…
SimpleSpeech 2: Towards Simple and Efficient Text-to-Speech with Flow-based Scalar Latent Transformer Diffusion Models
Dongchao Yang, Rongjie Huang, Yuanyuan Wang +5
Scaling Text-to-speech (TTS) to large-scale datasets has been demonstrated as an effective method for improving the diversity and naturalness of synthesized speech. At the high lev…
UniAudio 1.5: Large Language Model-driven Audio Codec is A Few-shot Audio Task Learner
Dongchao Yang, Haohan Guo, Yuanyuan Wang +5
The Large Language models (LLMs) have demonstrated supreme capabilities in text understanding and generation, but cannot be directly applied to cross-modal tasks without fine-tunin…
Audio Prompt Tuning for Universal Sound Separation
Yuzhuo Liu, Xubo Liu, Yan Zhao +4
Universal sound separation (USS) is a task to separate arbitrary sounds from an audio mixture. Existing USS systems are capable of separating arbitrary sources, given a few example…