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Tien-Hong Lo
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2020 – today
- 2024
- [i11]Tien-Hong Lo, Fu-An Chao, Tzu-I Wu, Yao-Ting Sung, Berlin Chen:
An Effective Automated Speaking Assessment Approach to Mitigating Data Scarcity and Imbalanced Distribution. CoRR abs/2404.07575 (2024) - 2023
- [c23]Fu-An Chao, Tien-Hong Lo, Tzu-I Wu, Yao-Ting Sung, Berlin Chen:
A Hierarchical Context-aware Modeling Approach for Multi-aspect and Multi-granular Pronunciation Assessment. INTERSPEECH 2023: 974-978 - [c22]Tzu-I Wu, Tien-Hong Lo, Fu-An Chao, Yao-Ting Sung, Berlin Chen:
Effective Neural Modeling Leveraging Readability Features for Automated Essay Scoring. SLaTE 2023: 81-85 - [c21]Jiun-Ting Li, Tien-Hong Lo, Bi-Cheng Yan, Yung-Chang Hsu, Berlin Chen:
Graph-Enhanced Transformer Architecture with Novel Use of CEFR Vocabulary Profile and Filled Pauses in Automated Speaking Assessment. SLaTE 2023: 109-113 - [i10]Fu-An Chao, Tien-Hong Lo, Tzu-I Wu, Yao-Ting Sung, Berlin Chen:
A Hierarchical Context-aware Modeling Approach for Multi-aspect and Multi-granular Pronunciation Assessment. CoRR abs/2305.18146 (2023) - 2022
- [c20]Tzu-I Wu, Tien-Hong Lo, Fu-An Chao, Yao-Ting Sung, Berlin Chen:
A Preliminary Study on Automated Speaking Assessment of English as a Second Language (ESL) Students. ROCLING 2022: 174-183 - [i9]Fu-An Chao, Tien-Hong Lo, Tzu-I Wu, Yao-Ting Sung, Berlin Chen:
3M: An Effective Multi-view, Multi-granularity, and Multi-aspect Modeling Approach to English Pronunciation Assessment. CoRR abs/2208.09110 (2022) - 2021
- [c19]Tien-Hong Lo, Yao-Ting Sung, Berlin Chen:
Improving End-To-End Modeling for Mispronunciation Detection with Effective Augmentation Mechanisms. APSIPA ASC 2021: 1049-1055 - [c18]Shih-Hsuan Chiu, Tien-Hong Lo, Fu-An Chao, Berlin Chen:
Cross-utterance Reranking Models with BERT and Graph Convolutional Networks for Conversational Speech Recognition. APSIPA ASC 2021: 1104-1110 - [c17]Shao-Wei Fan-Jiang, Bi-Cheng Yan, Tien-Hong Lo, Fu-An Chao, Berlin Chen:
Towards Robust Mispronunciation Detection and Diagnosis for L2 English Learners with Accent-Modulating Methods. ASRU 2021: 1065-1070 - [c16]Shih-Hsuan Chiu, Tien-Hong Lo, Berlin Chen:
Cross-sentence Neural Language Models for Conversational Speech Recognition. IJCNN 2021: 1-7 - [c15]You-Sheng Tsao, Tien-Hong Lo, Jiun-Ting Li, Shi-Yan Weng, Berlin Chen:
A Preliminary Study on Environmental Sound Classification Leveraging Large-Scale Pretrained Model and Semi-Supervised Learning. ROCLING 2021: 103-110 - [i8]Shih-Hsuan Chiu, Tien-Hong Lo, Berlin Chen:
Cross-sentence Neural Language Models for Conversational Speech Recognition. CoRR abs/2106.06922 (2021) - [i7]Shao-Wei Fan-Jiang, Bi-Cheng Yan, Tien-Hong Lo, Fu-An Chao, Berlin Chen:
Towards Robust Mispronunciation Detection and Diagnosis for L2 English Learners with Accent-Modulating Methods. CoRR abs/2108.11627 (2021) - [i6]Tien-Hong Lo, Yao-Ting Sung, Berlin Chen:
Improving End-To-End Modeling for Mispronunciation Detection with Effective Augmentation Mechanisms. CoRR abs/2110.08731 (2021) - 2020
- [c14]Shi-Yan Weng, Tien-Hong Lo, Berlin Chen:
An Effective Contextual Language Modeling Framework for Speech Summarization with Augmented Features. EUSIPCO 2020: 316-320 - [c13]Shao-Wei Fan-Jiang, Tien-Hong Lo, Berlin Chen:
Spoken Document Retrieval Leveraging Bert-Based Modeling and Query Reformulation. ICASSP 2020: 8144-8148 - [c12]Tien-Hong Lo, Fu-An Chao, Shi-Yan Weng, Berlin Chen:
The NTNU System at the Interspeech 2020 Non-Native Children's Speech ASR Challenge. INTERSPEECH 2020: 250-254 - [c11]Tien-Hong Lo, Shi-Yan Weng, Hsiu-Jui Chang, Berlin Chen:
An Effective End-to-End Modeling Approach for Mispronunciation Detection. INTERSPEECH 2020: 3027-3031 - [c10]Yu-Sen Cheng, Tien-Hong Lo, Berlin Chen:
Exploiting Text Prompts for the Development of an End-to-End Computer-Assisted Pronunciation Training System. ROCLING 2020: 290-303 - [i5]Tien-Hong Lo, Fu-An Chao, Shi-Yan Weng, Berlin Chen:
The NTNU System at the Interspeech 2020 Non-Native Children's Speech ASR Challenge. CoRR abs/2005.08433 (2020) - [i4]Tien-Hong Lo, Shi-Yan Weng, Hsiu-Jui Chang, Berlin Chen:
An Effective End-to-End Modeling Approach for Mispronunciation Detection. CoRR abs/2005.08440 (2020) - [i3]Shi-Yan Weng, Tien-Hong Lo, Berlin Chen:
An Effective Contextual Language Modeling Framework for Speech Summarization with Augmented Features. CoRR abs/2006.01189 (2020) - [i2]Wen-Ting Tseng, Tien-Hong Lo, Yung-Chang Hsu, Berlin Chen:
Effective FAQ Retrieval and Question Matching With Unsupervised Knowledge Injection. CoRR abs/2010.14049 (2020) - [i1]Yu-Sen Cheng, Chun-Liang Shih, Tien-Hong Lo, Wen-Ting Tseng, Berlin Chen:
Query Expansion System for the VoxCeleb Speaker Recognition Challenge 2020. CoRR abs/2011.02882 (2020)
2010 – 2019
- 2019
- [c9]Tien-Hong Lo, Berlin Chen:
Semi-supervised Training of Acoustic Models Leveraging Knowledge Transferred from Out-of-Domain Data. APSIPA 2019: 1400-1404 - [c8]Hsiao-Yun Lin, Tien-Hong Lo, Berlin Chen:
Enhanced Bert-Based Ranking Models for Spoken Document Retrieval. ASRU 2019: 601-606 - [c7]Ming-Jhang Yang, Fu-An Chao, Tien-Hong Lo, Berlin Chen:
使用生成對抗網路於強健式自動語音辨識的應用(Exploiting Generative Adversarial Network for Robustness Automatic Speech Recognition). ROCLING 2019: 212-225 - [c6]Hsiu-Jui Chang, Tien-Hong Lo, Tzu-En Liu, Berlin Chen:
探究端對端語音辨識於發音檢測與診斷(Investigating on Computer-Assisted Pronunciation Training Leveraging End-to-End Speech Recognition Techniques). ROCLING 2019: 266-280 - 2018
- [c5]Ying-Wen Chen, Tien-Hong Lo, Hsiu-Jui Chang, Wei-Cheng Chao, Berlin Chen:
會議語音辨識使用語者資訊之語言模型調適技術 (On the Use of Speaker-Aware Language Model Adaptation Techniques for Meeting Speech Recognition ) [In Chinese]. ROCLING 2018: 46-60 - [c4]Tien-Hong Lo, Berlin Chen:
探討聲學模型的合併技術與半監督鑑別式訓練於會議語音辨識之研究 (Investigating acoustic model combination and semi-supervised discriminative training for meeting speech recognition) [In Chinese]. ROCLING 2018: 78-80 - [c3]Wei-Cheng Chao, Hsiu-Jui Chang, Tien-Hong Lo, Berlin Chen:
探討鑑別式訓練聲學模型之類神經網路架構及優化方法的改進 (Discriminative Training of Acoustic Models Leveraging Improved Neural Network Architecture and Optimization Method) [In Chinese]. ROCLING 2018: 111-113 - 2017
- [j1]Tien-Hong Lo, Ying-Wen Chen, Kuan-Yu Chen, Hsin-Min Wang, Berlin Chen:
On the Use of Neural Network Modeling Techniques for Spoken Document Retrieval. Int. J. Comput. Linguistics Chin. Lang. Process. 22(2) (2017) - [c2]Tien-Hong Lo, Ying-Wen Chen, Kuan-Yu Chen, Hsin-Min Wang
, Berlin Chen:
Neural relevance-aware query modeling for spoken document retrieval. ASRU 2017: 466-473 - [c1]Tien-Hong Lo, Ying-Wen Chen, Berlin Chen, Kuan-Yu Chen, Hsin-Min Wang:
使用查詢意向探索與類神經網路於語音文件檢索之研究 (Exploring Query Intent and Neural Network modeling Techniques for Spoken Document Retrieval) [In Chinese]. ROCLING 2017: 149-151
Coauthor Index
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last updated on 2024-08-02 19:19 CEST by the dblp team
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