collaborators

5 papers

cs.CL2026

LOPA: Enhancing Spoken Language Assessment via Latent Ordinal Prototype Alignment

Hong-Yun Lin, Fu-An Chao, Bi-Cheng Yan +1

Fueled by increasing model scale and multimodal inputs, Multimodal Large Language Models (MLLMs) have emerged as a promising paradigm for Spoken Language Assessment (SLA). While ef…

cs.CL2026

Probing the Hidden Talent of ASR Foundation Models for L2 English Oral Assessment

Fu-An Chao, Bi-Cheng Yan, Berlin Chen

In this paper, we explore the untapped potential of Whisper, a well-established automatic speech recognition (ASR) foundation model, in the context of L2 spoken language assessment…

eess.AS2025

HiPPO: Exploring A Novel Hierarchical Pronunciation Assessment Approach for Spoken Languages

Bi-Cheng Yan, Hsin-Wei Wang, Fu-An Chao +3

Automatic pronunciation assessment (APA) seeks to quantify a second language (L2) learner's pronunciation proficiency in a target language by offering timely and fine-grained diagn…

cs.SD2025

An Effective Automated Speaking Assessment Approach to Mitigating Data Scarcity and Imbalanced Distribution

Tien-Hong Lo, Fu-An Chao, Tzu-I Wu +2

Automated speaking assessment (ASA) typically involves automatic speech recognition (ASR) and hand-crafted feature extraction from the ASR transcript of a learner's speech. Recentl…

eess.AS2025

Towards Efficient and Multifaceted Computer-assisted Pronunciation Training Leveraging Hierarchical Selective State Space Model and Decoupled Cross-entropy Loss

Fu-An Chao, Berlin Chen

Prior efforts in building computer-assisted pronunciation training (CAPT) systems often treat automatic pronunciation assessment (APA) and mispronunciation detection and diagnosis…