5 citations · 21 across the 24 of their papers we have counts for
26 papers
A Novel Sentence Stress Detection Framework Leveraging Auxiliary Word-Stress Modeling and Loss Optimization
Tien-Hong Lo, Fong-Chun Tsai, Ting-An Hung +3
Prosodic stress is a crucial aspect of automatic pronunciation assessment (APA), encompassing both sentence stress detection (SSD) and word stress detection (WSD). SSD highlights s…
T-SANDHI: Tone Sandhi-aware Adaptive Network with Decoupled Hybrid Injection for Low-resource Taiwanese Hokkien Speech Recognition
Hung-Yang Sung, Chien-Chun Wang, Tien-Hong Lo +3
In Taiwanese Hokkien automatic speech recognition (ASR), prior studies often treat tone sandhi as a major challenge under the assumption that models fail to process implicit phonol…
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…
Contextual Biasing for Streaming ASR via CTC-based Word Spotting
Kai-Chen Tsai, Tien-Hong Lo, Yun-Ting Sun +1
Contextual biasing is essential to improving the recognition of rare and domain-specific words in an automatic speech recognition (ASR) system. While numerous methods have been pro…
MALEFA: Multi-grAnularity Learning and Effective False Alarm Suppression for Zero-shot Keyword Spotting
Lo-Ya Li, Tien-Hong Lo, Jeih-Weih Hung +2
User-defined keyword spotting (KWS) without resorting to domain-specific pre-labeled training data is of fundamental importance in building adaptable and personalized voice interfa…
Efficient Dialect-Aware Modeling and Conditioning for Low-Resource Taiwanese Hakka Speech Processing
An-Ci Peng, Kuan-Tang Huang, Tien-Hong Lo +3
Taiwanese Hakka is a low-resource, endangered language that poses significant challenges for automatic speech recognition (ASR), including high dialectal variability and the presen…
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…
CLiFT-ASR: A Cross-Lingual Fine-Tuning Framework for Low-Resource Taiwanese Hokkien Speech Recognition
Hung-Yang Sung, Chien-Chun Wang, Kuan-Tang Huang +4
Automatic speech recognition (ASR) for low-resource languages such as Taiwanese Hokkien is difficult due to the scarcity of annotated data. However, direct fine-tuning on Han-chara…
An Effective Strategy for Modeling Score Ordinality and Non-uniform Intervals in Automated Speaking Assessment
Tien-Hong Lo, Szu-Yu Chen, Yao-Ting Sung +1
A recent line of research on automated speaking assessment (ASA) has benefited from self-supervised learning (SSL) representations, which capture rich acoustic and linguistic patte…
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…
Beyond Modality Limitations: A Unified MLLM Approach to Automated Speaking Assessment with Effective Curriculum Learning
Yu-Hsuan Fang, Tien-Hong Lo, Yao-Ting Sung +1
Traditional Automated Speaking Assessment (ASA) systems exhibit inherent modality limitations: text-based approaches lack acoustic information while audio-based methods miss semant…
The NTNU System at the S&I Challenge 2025 SLA Open Track
Hong-Yun Lin, Tien-Hong Lo, Yu-Hsuan Fang +4
A recent line of research on spoken language assessment (SLA) employs neural models such as BERT and wav2vec 2.0 (W2V) to evaluate speaking proficiency across linguistic and acoust…
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…
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…
Improving End-To-End Modeling for Mispronunciation Detection with Effective Augmentation Mechanisms
Tien-Hong Lo, Yao-Ting Sung, Berlin Chen
Recently, end-to-end (E2E) models, which allow to take spectral vector sequences of L2 (second-language) learners' utterances as input and produce the corresponding phone-level seq…
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…
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…
Query Expansion System for the VoxCeleb Speaker Recognition Challenge 2020
Yu-Sen Cheng, Chun-Liang Shih, Tien-Hong Lo +2
In this report, we describe our submission to the VoxCeleb Speaker Recognition Challenge (VoxSRC) 2020. Two approaches are adopted. One is to apply query expansion on speaker verif…
Effective FAQ Retrieval and Question Matching With Unsupervised Knowledge Injection
Wen-Ting Tseng, Tien-Hong Lo, Yung-Chang Hsu +1
Frequently asked question (FAQ) retrieval, with the purpose of providing information on frequent questions or concerns, has far-reaching applications in many areas, where a collect…
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…