2 citations · 2 across the 4 of their papers we have counts for
5 papers
MSI-Bench: Evaluating Multi-Speaker Voice Interaction for Collaborative AI Agents
Chenxu Xiong, Dongming Shen, Yuzhi Tang +3
Voice provides a natural and immediate interface for AI agents. Many settings in which voice agents could be useful, including meetings, households, and collaborative work, are inh…
Instruct-FD: Can Your Full-Duplex Speech System Follow Turn-Taking Instructions?
Yuzhi Tang, Wentao Ma, Xiling Zhao +17
Current full-duplex (FD) spoken dialogue systems can produce fluid interactions, yet it remains unclear whether they can adapt their turn-taking behavior when explicitly instructed…
IHBench: Evaluating Post-Interruption Recovery in Voice Agents with Structured Workflows
Ahmad Salimi, Wentao Ma, Yuzhi Tang +3
Voice agents deployed in structured workflows (customer service, healthcare scheduling, account management) must handle frequent user interruptions while maintaining progress throu…
EmergentTTS-Eval: Evaluating TTS Models on Complex Prosodic, Expressiveness, and Linguistic Challenges Using Model-as-a-Judge
Ruskin Raj Manku, Yuzhi Tang, Xingjian Shi +2
Text-to-Speech (TTS) benchmarks often fail to capture how well models handle nuanced and semantically complex text. Building on , we introduce $\textit{Emerge…
Mamba-based Deep Learning Approach for Sleep Staging on a Wireless Multimodal Wearable System without Electroencephalography
Andrew H. Zhang, Alex He-Mo, Richard Fei Yin +9
Study Objectives: We investigate a Mamba-based deep learning approach for sleep staging on signals from ANNE One (Sibel Health, Evanston, IL), a non-intrusive dual-module wireless…