Unsupervised Neural Word Segmentation for Chinese via Segmental Language Modeling (D18-1)
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| Challenge: | Existing approaches to unsupervised Chinese word segmentation (CWS) are discriminative and generative, but they are non-trivial. |
| Approach: | They propose a neural generative model for fully unsupervised Chinese word segmentation (CWS) their approach explicitly focuses on the segmental nature of Chinese, and preserves several properties of language models. |
| Outcome: | The proposed model achieves competitive performance to the state-of-the-art models on four datasets from SIGHAN 2005 bakeoff. |
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Mieradilijiang Maimaiti, Yang Liu, Yuanhang Zheng, Gang Chen, Kaiyu Huang, Ji Zhang, Huanbo Luan, Maosong Sun
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| Challenge: | Recent years have seen remarkable success in the use of deep neural networks on Chinese word segmentation (CWS) however, the performance of CWS systems has gradually reached a plateau with the rapid development of deep networks. |
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| Challenge: | Recent Chinese word segmentation models tend to learn the segmentation knowledge through in-vocabulary words rather than understanding the meaning of the entire context. |
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| Challenge: | Using word-based models, we compare word-oriented models with char-based ones . word-driven models are more vulnerable to data sparsity and the presence of out-of-vocabulary words . |
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| Challenge: | Existing models of word learning do not account for the long-range dependencies manifest in language and that are easily captured by recurrent neural networks. |
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State-of-the-art Chinese Word Segmentation with Bi-LSTMs (D18-1)
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| Challenge: | A wide variety of neural-network architectures have been proposed for the task of Chinese word segmentation. |
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CWSeg: An Efficient and General Approach to Chinese Word Segmentation (2023.acl-industry)
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| Challenge: | Existing methods for Chinese word segmentation have achieved state-of-the-art performance, but they pose challenges in the deployment. |
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| Challenge: | Existing methods for unsupervised Chinese word segmentation exploit shallow semantic information, which can miss important context. |
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More than Text: Multi-modal Chinese Word Segmentation (2021.acl-short)
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| Challenge: | Currently, word segmentation is performed in many languages without word delimiters. |
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Improved Unsupervised Chinese Word Segmentation Using Pre-trained Knowledge and Pseudo-labeling Transfer (2023.emnlp-main)
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| Challenge: | Existing approaches to unsupervised Chinese word segmentation require multiple inferences to perform word segmenting. |
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