8 papers
[b]=[d]-[t]+[p]: Self-supervised Speech Models Discover Phonological Vector Arithmetic
Kwanghee Choi, Eunjung Yeo, Cheol Jun Cho +2
Self-supervised speech models (S3Ms) are known to encode rich phonetic information, yet how this information is structured remains underexplored. We conduct a comprehensive study a…
HASS: Hierarchical Simulation of Logopenic Aphasic Speech for Scalable PPA Detection
Harrison Li, Kevin Wang, Cheol Jun Cho +13
Building a diagnosis model for primary progressive aphasia (PPA) has been challenging due to the data scarcity. Collecting clinical data at scale is limited by the high vulnerabili…
Self-Supervised Speech Models Encode Phonetic Context via Position-dependent Orthogonal Subspaces
Kwanghee Choi, Eunjung Yeo, Cheol Jun Cho +2
Transformer-based self-supervised speech models (S3Ms) are often described as contextualized, yet what this entails remains unclear. Here, we focus on how a single frame-level S3M…
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…
HuPER: A Human-Inspired Framework for Phonetic Perception
Chenxu Guo, Jiachen Lian, Yisi Liu +4
We propose HuPER, a human-inspired framework that models phonetic perception as adaptive inference over acoustic-phonetics evidence and linguistic knowledge. With only 100 hours of…
Teaching Machines to Speak Using Articulatory Control
Akshay Anand, Chenxu Guo, Cheol Jun Cho +2
Current speech production systems predominantly rely on large transformer models that operate as black boxes, providing little interpretability or grounding in the physical mechani…