1 citations · 1 across the 2 of their papers we have counts for
6 papers
SALMONN-2: Advancing General-Purpose Hearing Abilities with Self-Supervised Representations
Xiaoyu Yang, Xuenan Xu, Wenyi Yu +10
Recent audio large language models (ALLMs) are typically built upon audio encoders trained with large amounts of supervised data. Since self-supervised learning (SSL) audio encoder…
SPEAR: A Unified SSL Framework for Learning Speech and Audio Representations
Xiaoyu Yang, Yifan Yang, Zengrui Jin +5
Self-supervised learning (SSL) has significantly advanced acoustic representation learning. However, most existing models are optimised for either speech or audio event understandi…
AuDirector: A Self-Reflective Closed-Loop Framework for Immersive Audio Storytelling
Yiming Ren, Xuenan Xu, Ziyang Zhang +3
Despite advances in text and visual generation, creating coherent long-form audio narratives remains challenging. Existing frameworks often exhibit limitations such as mismatched c…
Bayesian Speech Synthesizers Can Learn from Multiple Teachers
Ziyang Zhang, Yifan Gao, Xuenan Xu +3
Text-to-Speech (TTS) is inherently a "one-to-many" mapping characterized by intrinsic uncertainty, yet current paradigms often oversimplify it into a deterministic regression task.…
HoliAntiSpoof: Audio LLM for Holistic Speech Anti-Spoofing
Xuenan Xu, Yiming Ren, Liwei Liu +5
Recent advances in speech synthesis and editing have made speech spoofing increasingly challenging. However, most existing methods treat spoofing as binary classification, overlook…
Can Audio Large Language Models Verify Speaker Identity?
Yiming Ren, Xuenan Xu, Baoxiang Li +2
This paper investigates adapting Audio Large Language Models (ALLMs) for speaker verification (SV). We reformulate SV as an audio question-answering task and conduct comprehensive…