Ke-Han Lu


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ntust-nlp-2 at ROCLING-2021 Shared Task: BERT-based semantic analyzer with word-level information
Ke-Han Lu | Kuan-Yu Chen
Proceedings of the 33rd Conference on Computational Linguistics and Speech Processing (ROCLING 2021)

In this paper, we proposed a BERT-based dimensional semantic analyzer, which is designed by incorporating with word-level information. Our model achieved three of the best results in four metrics on “ROCLING 2021 Shared Task: Dimensional Sentiment Analysis for Educational Texts”. We conducted a series of experiments to compare the effectiveness of different pre-trained methods. Besides, the results also proofed that our method can significantly improve the performances than classic methods. Based on the experiments, we also discussed the impact of model architectures and datasets.

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2020福爾摩沙臺語語音辨識比賽之初步實驗 (A Preliminary Study of Formosa Speech Recognition Challenge 2020 – Taiwanese ASR)
Fu-Hao Yu | Ke-Han Lu | Yi-Wei Wang | Wei-Zhe Chang | Wei-Kai Huang | Kuan-Yu Chen
International Journal of Computational Linguistics & Chinese Language Processing, Volume 26, Number 1, June 2021