14 citations · 15 across the 4 of their papers we have counts for
4 papers
SpeechGym: An Audio-Native Gym for Training Voice Agents via Reinforcement Learning
Jiajun Fan, Jingyuan Li, Prashanth Gurunath Shivakumar +6
Voice agents must call tools and hold multi-turn dialogue entirely through speech, yet the dominant paradigm trains them in text. Existing frameworks either cascade TTS and ASR aro…
Can We Read the Mind of an Audio LLM? A Verbalizable, Multilingual Middle-Layer Workspace
Jiajun Fan, Jingyuan Li, Prashanth Gurunath Shivakumar +8
An audio language model is a black box in a specific way: we see what it says, never what it works out on the way there, and chain-of-thought monitoring helps only if the model wri…
Rhythm-controllable Attention with High Robustness for Long Sentence Speech Synthesis
Dengfeng Ke, Yayue Deng, Yukang Jia +6
Regressive Text-to-Speech (TTS) system utilizes attention mechanism to generate alignment between text and acoustic feature sequence. Alignment determines synthesis robustness (e.g…
PROCTER: PROnunciation-aware ConTextual adaptER for personalized speech recognition in neural transducers
Rahul Pandey, Roger Ren, Qi Luo +7
End-to-End (E2E) automatic speech recognition (ASR) systems used in voice assistants often have difficulties recognizing infrequent words personalized to the user, such as names an…