Results 11 to 20 of about 25,624 (260)
Segmentation of Written Words in French [PDF]
Language and Speech, 2012 Syllabification of spoken words has been largely used to define syllabic properties of written words, such as the number of syllables or syllabic boundaries. By contrast, some authors proposed that the functional structure of written words stems from visuo-orthographic features rather than from the transposition of phonological structure into the ...
Chetail, Fabienne, Content, Alain
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On the Difficulty of Segmenting Words with Attention [PDF]
Proceedings of the Second Workshop on Insights from Negative Results in NLP, 2021 Word segmentation, the problem of finding word boundaries in speech, is of interest for a range of tasks. Previous papers have suggested that for sequence-to-sequence models trained on tasks such as speech translation or speech recognition, attention can be used to locate and segment the words.
Ramon Sanabria +2 more
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An Algorithm Rapidly Segmenting Chinese Sentences into Individual Words [PDF]
MATEC Web of Conferences, 2019 This paper proposes an improved Trie tree structure. The tree node records the position information of the characters participating in the word formation, and the child node uses the hash search mechanism.
Xiong Zhibin
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Combining segmenter and chunker for Chinese word segmentation [PDF]
Proceedings of the second SIGHAN workshop on Chinese language processing -, 2003 Our proposed method is to use a Hidden Markov Model-based word segmenter and a Support Vector Machine-based chunker for Chinese word segmentation. Firstly, input sentences are analyzed by the Hidden Markov Model-based word segmenter. The word segmenter produces n-best word candidates together with some class information and confidence measures ...
Masayuki Asahara +3 more
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A Japanese Word Segmentation Proposal [PDF]
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, 2019 Current Japanese word segmentation methods, that use a morpheme-based approach, may produce different segmentations for the same strings. This occurs when these strings appear in different sentences. The cause is the influence of different contexts around these strings affecting the probabilistic models used in segmentation algorithms.
Stalin Aguirre, Josafá Aguiar
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Hybrid Feature Fusion Learning Towards Chinese Chemical Literature Word Segmentation
IEEE Access, 2021 The rapid increase in the number of chemical science literature has brought challenges to researchers in search and data analysis. For many chemical scientific literature, extracting information from text and using knowledge is the focus of research ...
Xiang Li +4 more
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Universal Word Segmentation: Implementation and Interpretation [PDF]
Transactions of the Association for Computational Linguistics, 2021 Word segmentation is a low-level NLP task that is non-trivial for a considerable number of languages. In this paper, we present a sequence tagging framework and apply it to word segmentation for a wide range of languages with different writing systems and typological characteristics.
Yan Shao +2 more
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Adaptive Chinese word segmentation [PDF]
Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics - ACL '04, 2004 This paper presents a Chinese word segmentation system which can adapt to different domains and standards. We first present a statistical framework where domain-specific words are identified in a unified approach to word segmentation based on linear models. We explore several features and describe how to create training data by sampling.
Jianfeng Gao +6 more
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Domain-Specific Chinese Word Segmentation Based on Bi-Directional Long-Short Term Memory Model
IEEE Access, 2019 Most of the current word segmentation methods are rule-based and traditional machine learning methods. Universal word segmentation tools do not work well in the field such as metallurgy. Domain-specific Chinese word segmentation is rarely studied.
Dangguo Shao +6 more
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Feature Extraction and Analysis of Natural Language Processing for Deep Learning English Language
IEEE Access, 2020 NLP (Natural Language Processing) is a technology that enables computers to understand human languages. Deep-level grammatical and semantic analysis usually uses words as the basic unit, and word segmentation is usually the primary task of NLP.
Dongyang Wang, Junli Su, Hongbin Yu
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