4 citations · 5 across the 4 of their papers we have counts for
6 papers
PEDBench: Can Speech Models Detect Phonetic Errors?
Zhonghao Shi, Zackary Rackauckas, Jasmine Yip +9
Phonetic error detection (PED) aims to identify phoneme-level substitutions, deletions, and insertions and is essential for educational and clinical speech assessment and intervent…
ChildVox: A Speech, Audio, and Large Audio-Language Model Benchmark in Understanding and Characterizing Sound across Childhood
Tiantian Feng, Anfeng Xu, Xuan Shi +10
We present ChildVox, a novel benchmark for characterizing the diverse acoustic signals through which children communicate. Specifically, ChildVox follows the full developmental tra…
Personalized Socially Assistive Robots With End-to-End Speech-Language Models For Well-Being Support
Mengxue Fu, Zhonghao Shi, Minyu Huang +4
Socially assistive robots (SARs) have shown great potential for supplementing well-being support. However, prior studies have found that existing dialogue pipelines for SARs remain…
Examining Test-Time Adaptation for Personalized Child Speech Recognition
Zhonghao Shi, Xuan Shi, Anfeng Xu +4
Automatic speech recognition (ASR) models often experience performance degradation due to data domain shifts introduced at test time, a challenge that is further amplified for chil…
How Can Large Language Models Enable Better Socially Assistive Human-Robot Interaction: A Brief Survey
Zhonghao Shi, Ellen Landrum, Amy O' Connell +5
Socially assistive robots (SARs) have shown great success in providing personalized cognitive-affective support for user populations with special needs such as older adults, childr…
Build Your Own Robot Friend: An Open-Source Learning Module for Accessible and Engaging AI Education
Zhonghao Shi, Allison O'Connell, Zongjian Li +5
As artificial intelligence (AI) is playing an increasingly important role in our society and global economy, AI education and literacy have become necessary components in college a…