19 citations · 21 across the 11 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…
Do Speech Emphasis Models Generalize across Languages and Emotions?
Megan Wei, Deepali Aneja, Jiaqi Su +3
Prosodic emphasis varies across languages, emotions, and speaking styles, yet existing emphasis detection models are largely trained and evaluated on monolingual neutral read speec…
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…
Gencho: Room Impulse Response Generation from Reverberant Speech and Text via Diffusion Transformers
Jackie Lin, Jiaqi Su, Nishit Anand +3
Blind room impulse response (RIR) estimation is a core task for capturing and transferring acoustic properties; yet existing methods often suffer from limited modeling capability a…