8 citations · 15 across the 33 of their papers we have counts for
7 papers · 1 filter
KIRA: A Full-Stack Reading Screening System with Dual-Pathway Analysis for Children
Maggie Dong, Rohit Mekkoth, Zixuan Wang +3
Early-grade reading screening is critical for identifying children at risk of reading difficulty. Existing AI-based screeners are often limited in the scope of their analyses and e…
S-MARC: Causal Streaming Reasoning for Full-Duplex Conversational Behavior Modeling
Dingkun Zhou, Shuchang Pan, Jiachen Lian +11
Human conversation is organized by an implicit chain of thought and manifests as temporally structured conversational behaviors. Capturing this perceptual pathway is critical for b…
Enabling Conversational Behavior Reasoning Capabilities in Full-Duplex Speech
Shuchang Pan, Siddharth Banerjee, Dhruv Hebbar +9
Human conversation is organized by an implicit chain of thoughts that manifests as timed speech acts. Capturing this causal pathway is key to building natural full-duplex interacti…
EMO-Reasoning: Benchmarking Emotional Reasoning Capabilities in Spoken Dialogue Systems
Jingwen Liu, Kan Jen Cheng, Jiachen Lian +8
Speech emotions play a crucial role in human-computer interaction, shaping engagement and context-aware communication. Despite recent advances in spoken dialogue systems, a holisti…
K-Function: Joint Pronunciation Transcription and Feedback for Evaluating Kids Language Function
Shuhe Li, Chenxu Guo, Jiachen Lian +18
Evaluating young children's language is challenging for automatic speech recognizers due to high-pitched voices, prolonged sounds, and limited data. We introduce K-Function, a fram…
Full-Duplex-Bench: A Benchmark to Evaluate Full-duplex Spoken Dialogue Models on Turn-taking Capabilities
Guan-Ting Lin, Jiachen Lian, Tingle Li +4
Spoken dialogue modeling poses challenges beyond text-based language modeling, requiring real-time interaction, turn-taking, and backchanneling. While most Spoken Dialogue Models (…
Towards Hierarchical Spoken Language Dysfluency Modeling
Jiachen Lian, Gopala Anumanchipalli
Speech disfluency modeling is the bottleneck for both speech therapy and language learning. However, there is no effective AI solution to systematically tackle this problem. We sol…