Titlebook: Computational and Corpus Approaches to Chinese Language Learning; Xiaofei Lu,Berlin Chen Book 2019 Springer Nature Singapore Pte Ltd. 2019

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https://doi.org/10.1007/3-540-06705-1uires not only knowledge of language as a functional system and knowledge of language learning as a human socio-cognitive endeavor but also expanded communication across domains traditionally separated by differences in the methodology of knowledge construction. This chapter focuses on the usage-bas

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Ryuzo Sato,Rama V. Ramachandranigate both the process and outcome of data-driven adapting using .-., a case study was conducted, involving a team of teachers working on the adaptation of texts. Results are discussed in terms of the effectiveness of the data-driven adapting practices by teachers in a classroom setting. Overall, th

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Ryuzo Sato,Rama V. Ramachandranhe approach, together with comparisons with previous observations. Not only can the present approach provide a clearer and more nuanced picture than what introspection allows, it also enables us to go beyond the spoken versus written dichotomy and gain a broader perspective on stylistic variation.

我正派

Symmetry of High-Tc Superconductorsnstrate that learners generally use . in speech with a low frequency and a high degree of accuracy. Significant increase in frequency of use is observed between beginner and intermediate learners, while that in accuracy is observed between intermediate and advanced learners. Evidence from the curren

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Conference proceedings 20061st editionon diagnosis process can benefit from the use of these specifically trained acoustic models. For this purpose, we recast mispronunciation diagnosis as a classification problem and a set of indicative features are derived. A series of experiments on a Mandarin Chinese mispronunciation detection and d

高腳酒杯

Symmetry of High-Tc Superconductorstems. In this chapter, we describe two representative Chinese learner corpora: the HSK Dynamic Composition Corpus constructed by Beijing Language and Culture University and the TOCFL Learner Corpus built by National Taiwan Normal University. In addition, we introduce several evaluations based on bot

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