5 citations · 14 across the 13 of their papers we have counts for
14 papers
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…
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…
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…
A Hierarchical Context-aware Modeling Approach for Multi-aspect and Multi-granular Pronunciation Assessment
Fu-An Chao, Tien-Hong Lo, Tzu-I Wu +2
Automatic Pronunciation Assessment (APA) plays a vital role in Computer-assisted Pronunciation Training (CAPT) when evaluating a second language (L2) learner's speaking proficiency…
3M: An Effective Multi-view, Multi-granularity, and Multi-aspect Modeling Approach to English Pronunciation Assessment
Fu-An Chao, Tien-Hong Lo, Tzu-I Wu +2
As an indispensable ingredient of computer-assisted pronunciation training (CAPT), automatic pronunciation assessment (APA) plays a pivotal role in aiding self-directed language le…
Cross-domain Single-channel Speech Enhancement Model with Bi-projection Fusion Module for Noise-robust ASR
Fu-An Chao, Jeih-weih Hung, Berlin Chen
In recent decades, many studies have suggested that phase information is crucial for speech enhancement (SE), and time-domain single-channel speech enhancement techniques have show…
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…
Cross-utterance Reranking Models with BERT and Graph Convolutional Networks for Conversational Speech Recognition
Shih-Hsuan Chiu, Tien-Hong Lo, Fu-An Chao +1
How to effectively incorporate cross-utterance information cues into a neural language model (LM) has emerged as one of the intriguing issues for automatic speech recognition (ASR)…
The NTNU Taiwanese ASR System for Formosa Speech Recognition Challenge 2020
Fu-An Chao, Tien-Hong Lo, Shi-Yan Weng +3
This paper describes the NTNU ASR system participating in the Formosa Speech Recognition Challenge 2020 (FSR-2020) supported by the Formosa Speech in the Wild project (FSW). FSR-20…
The NTNU System at the Interspeech 2020 Non-Native Children's Speech ASR Challenge
Tien-Hong Lo, Fu-An Chao, Shi-Yan Weng +1
This paper describes the NTNU ASR system participating in the Interspeech 2020 Non-Native Children's Speech ASR Challenge supported by the SIG-CHILD group of ISCA. This ASR shared…