7 papers · 1 filter
COALA: Robust Contextualized Speech-augmented Language Modeling for ASR via Contrastive Regularizer and Biasing Score Estimation
Jhih-Rong Guo, Bi-Cheng Yan, Tien-Hong Lo +1
Contextual biasing seeks to integrate external knowledge into automatic speech recognition (ASR) systems to accurately recognize domain-specific entities. In this paper, we propose…
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…
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…
Multi-task Pretraining for Enhancing Interpretable L2 Pronunciation Assessment
Jiun-Ting Li, Bi-Cheng Yan, Yi-Cheng Wang +1
Automatic pronunciation assessment (APA) analyzes second-language (L2) learners' speech by providing fine-grained pronunciation feedback at various linguistic levels. Most existing…
Automated Speaking Assessment of Conversation Tests with Novel Graph-based Modeling on Spoken Response Coherence
Jiun-Ting Li, Bi-Cheng Yan, Tien-Hong Lo +3
Automated speaking assessment in conversation tests (ASAC) aims to evaluate the overall speaking proficiency of an L2 (second-language) speaker in a setting where an interlocutor i…
An Effective Context-Balanced Adaptation Approach for Long-Tailed Speech Recognition
Yi-Cheng Wang, Li-Ting Pai, Bi-Cheng Yan +3
End-to-end (E2E) automatic speech recognition (ASR) models have become standard practice for various commercial applications. However, in real-world scenarios, the long-tailed natu…