Early Word Segmentation Behind the Mask [PDF]
Frontiers in Psychology, 2022 Infants have been shown to rely both on auditory and visual cues when processing speech. We investigated the impact of COVID-related changes, in particular of face masks, in early word segmentation abilities.
Sónia Frota +4 more
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Visual Word Segmentation Cues in Tibetan Reading: Comparing Dictionary-Based and Psychological Word Segmentation [PDF]
Journal of Eye Movement ResearchThis study utilized eye-tracking technology to explore the role of visual word segmentation cues in Tibetan reading, with a particular focus on the effects of dictionary-based and psychological word segmentation on reading and lexical recognition.
Dingyi Niu +4 more
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A hybrid Chinese word segmentation model for quality management-related texts based on transfer learning. [PDF]
PLoS ONE, 2022 Text information mining is a key step to data-driven automatic/semi-automatic quality management (QM). For Chinese texts, a word segmentation algorithm is necessary for pre-processing since there are no explicit marks to define word boundaries.
Peihan Wen, Linhan Feng, Tian Zhang
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The Effect of Visual Word Segmentation Cues in Tibetan Reading [PDF]
Brain SciencesBackground/Objectives: In languages with within-word segmentation cues, the removal or replacement of these cues in a text hinders reading and lexical recognition, and adversely affects saccade target selection during reading.
Danhui Wang +3 more
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The Influence of Contextual Predictability on Word Segmentation in Chinese Reading: An Eye-Tracking Study [PDF]
Behavioral SciencesWord segmentation is a fundamental component of lexical processing, and Chinese reading—lacking inter-word spacing—requires readers to identify word boundaries based on prior experience.
Mengchuan Song +3 more
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Comparing neural- and N-gram-based language models for word segmentation. [PDF]
J Assoc Inf Sci Technol, 2019 Word segmentation is the task of inserting or deleting word boundary characters in order to separate character sequences that correspond to words in some language.
Doval Y, Gómez-Rodríguez C.
europepmc +4 more sources
Nonparametric Bayesian Semi-supervised Word Segmentation [PDF]
Transactions of the Association for Computational Linguistics, 2021 This paper presents a novel hybrid generative/discriminative model of word segmentation based on nonparametric Bayesian methods. Unlike ordinary discriminative word segmentation which relies only on labeled data, our semi-supervised model also leverages a huge amounts of unlabeled text to automatically learn new “words”, and further constrains them by
Ryo Fujii, Ryo Domoto, Daichi Mochihashi
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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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The effect of morpheme positional frequency on tibetan novel word acquisition: An eye-tracking study. [PDF]
PLoS ONEWord segmentation is crucial for reading in unspaced languages like Tibetan, where readers rely on high-level cues like morpheme positional frequency (the statistical likelihood of a morpheme appearing at the beginning or end of a word).
Dingyi Niu, Jing Tian
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Semantic Segmentation Method of Tibetan Sentences [PDF]
Jisuanji gongcheng, 2020 Sentences are characters or words that are combined according to grammatical rules.Semantic segmentation is a decoding problem of sentence combination rules,that is,parsing the meaning of sentences.If the semantic analysis is performed directly after the
ROU Te, SE Chajia, CAI Rangjia
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