3 citations · 12 across the 19 of their papers we have counts for
20 papers
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…
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…
MuFFIN: Multifaceted Pronunciation Feedback Model with Interactive Hierarchical Neural Modeling
Bi-Cheng Yan, Ming-Kang Tsai, Berlin Chen
Computer-assisted pronunciation training (CAPT) manages to facilitate second-language (L2) learners to practice pronunciation skills by offering timely and instructive feedback. To…
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…
Mitigating Data Imbalance in Automated Speaking Assessment
Fong-Chun Tsai, Kuan-Tang Huang, Bi-Cheng Yan +2
Automated Speaking Assessment (ASA) plays a crucial role in evaluating second-language (L2) learners proficiency. However, ASA models often suffer from class imbalance, leading to…
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…
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…
ConPCO: Preserving Phoneme Characteristics for Automatic Pronunciation Assessment Leveraging Contrastive Ordinal Regularization
Bi-Cheng Yan, Wei-Cheng Chao, Jiun-Ting Li +4
Automatic pronunciation assessment (APA) manages to evaluate the pronunciation proficiency of a second language (L2) learner in a target language. Existing efforts typically draw o…
DANCER: Entity Description Augmented Named Entity Corrector for Automatic Speech Recognition
Yi-Cheng Wang, Hsin-Wei Wang, Bi-Cheng Yan +2
End-to-end automatic speech recognition (E2E ASR) systems often suffer from mistranscription of domain-specific phrases, such as named entities, sometimes leading to catastrophic f…
Preserving Phonemic Distinctions for Ordinal Regression: A Novel Loss Function for Automatic Pronunciation Assessment
Bi-Cheng Yan, Hsin-Wei Wang, Yi-Cheng Wang +3
Automatic pronunciation assessment (APA) manages to quantify the pronunciation proficiency of a second language (L2) learner in a language. Prevailing approaches to APA normally le…
AVATAR: Robust Voice Search Engine Leveraging Autoregressive Document Retrieval and Contrastive Learning
Yi-Cheng Wang, Tzu-Ting Yang, Hsin-Wei Wang +2
Voice, as input, has progressively become popular on mobiles and seems to transcend almost entirely text input. Through voice, the voice search (VS) system can provide a more natur…
Effective Cross-Utterance Language Modeling for Conversational Speech Recognition
Bi-Cheng Yan, Hsin-Wei Wang, Shih-Hsuan Chiu +2
Conversational speech normally is embodied with loose syntactic structures at the utterance level but simultaneously exhibits topical coherence relations across consecutive utteran…
Exploring Non-Autoregressive End-To-End Neural Modeling For English Mispronunciation Detection And Diagnosis
Hsin-Wei Wang, Bi-Cheng Yan, Hsuan-Sheng Chiu +2
End-to-end (E2E) neural modeling has emerged as one predominant school of thought to develop computer-assisted language training (CAPT) systems, showing competitive performance to…
Maximum F1-score training for end-to-end mispronunciation detection and diagnosis of L2 English speech
Bi-Cheng Yan, Shao-Wei Fan Jiang, Fu-An Chao +1
End-to-end (E2E) neural models are increasingly attracting attention as a promising modeling approach for mispronunciation detection and diagnosis (MDD). Typically, these models ar…
Towards Robust Mispronunciation Detection and Diagnosis for L2 English Learners with Accent-Modulating Methods
Shao-Wei Fan Jiang, Bi-Cheng Yan, Tien-Hong Lo +2
With the acceleration of globalization, more and more people are willing or required to learn second languages (L2). One of the major remaining challenges facing current mispronunc…
TENET: A Time-reversal Enhancement Network for Noise-robust ASR
Fu-An Chao, Shao-Wei Fan Jiang, Bi-Cheng Yan +2
Due to the unprecedented breakthroughs brought about by deep learning, speech enhancement (SE) techniques have been developed rapidly and play an important role prior to acoustic m…
End-to-End Mispronunciation Detection and Diagnosis From Raw Waveforms
Bi-Cheng Yan, Berlin Chen
Mispronunciation detection and diagnosis (MDD) is designed to identify pronunciation errors and provide instructive feedback to guide non-native language learners, which is a core…
An End-to-End Mispronunciation Detection System for L2 English Speech Leveraging Novel Anti-Phone Modeling
Bi-Cheng Yan, Meng-Che Wu, Hsiao-Tsung Hung +1
Mispronunciation detection and diagnosis (MDD) is a core component of computer-assisted pronunciation training (CAPT). Most of the existing MDD approaches focus on dealing with cat…