7 citations · 7 across the 8 of their papers we have counts for
5 papers · 1 filter
ParA-LLM: A Unified Approach to Paralinguistic and Acoustic Speech Understanding
Nishit Anand, Jiaqi Su, Ke Chen +5
Recent advances in Audio LLMs have achieved human-level speech recognition, yet existing systems struggle to capture paralinguistic aspects such as speaker traits, expressive varia…
VoiceDesigner: Text-to-Voice Generation and Editing via Unified Diffusion Modeling and Data Augmentation
Jiarui Hai, Karan Thakkar, Ke Chen +5
Recent breakthroughs in generative models have made text-to-voice generation (TTV) possible, enabling the synthesis of speech directly from textual voice descriptions. However, exi…
Taming Audio VAEs via Target-KL Regularization
Prem Seetharaman, Rithesh Kumar
Latent diffusion models have emerged as the dominant paradigm for many generation tasks including audio generation such as text-to-audio, text-to-music and text-to-speech. A key co…
AudioChat: Unified Audio Storytelling, Editing, and Understanding with Transfusion Forcing
William Chen, Prem Seetharaman, Rithesh Kumar +4
Despite recent breakthroughs, audio foundation models struggle in processing complex multi-source acoustic scenes. We refer to this challenging domain as audio stories, which can h…
TAC: Timestamped Audio Captioning
Sonal Kumar, Prem Seetharaman, Ke Chen +8
Large Audio Language Models struggle to disentangle overlapping events in complex acoustic scenes, yielding temporally inconsistent captions and frequent hallucinations. We introdu…