1 citations · 2 across the 15 of their papers we have counts for
16 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…
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…
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…
Enhancing Code-Switching ASR Leveraging Non-Peaky CTC Loss and Deep Language Posterior Injection
Tzu-Ting Yang, Hsin-Wei Wang, Yi-Cheng Wang +1
Code-switching-where multilingual speakers alternately switch between languages during conversations-still poses significant challenges to end-to-end (E2E) automatic speech recogni…
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…
Zero-Shot Text-to-Speech as Golden Speech Generator: A Systematic Framework and its Applicability in Automatic Pronunciation Assessment
Tien-Hong Lo, Meng-Ting Tsai, Yao-Ting Sung +1
Second language (L2) learners can improve their pronunciation by imitating golden speech, especially when the speech that aligns with their respective speech characteristics. This…
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…
An Effective Mixture-Of-Experts Approach For Code-Switching Speech Recognition Leveraging Encoder Disentanglement
Tzu-Ting Yang, Hsin-Wei Wang, Yi-Cheng Wang +2
With the massive developments of end-to-end (E2E) neural networks, recent years have witnessed unprecedented breakthroughs in automatic speech recognition (ASR). However, the codes…
Leveraging Language ID to Calculate Intermediate CTC Loss for Enhanced Code-Switching Speech Recognition
Tzu-Ting Yang, Hsin-Wei Wang, Berlin Chen
In recent years, end-to-end speech recognition has emerged as a technology that integrates the acoustic, pronunciation dictionary, and language model components of the traditional…
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…