Vietnamese Word Segmentation
6 papers with code • 0 benchmarks • 0 datasets
Benchmarks
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Most implemented papers
A hybrid approach to Vietnamese word segmentation
Word segmentation is the very first task for Vietnamese language processing.
A Fast and Accurate Vietnamese Word Segmenter
We propose a novel approach to Vietnamese word segmentation.
Vietnamese Word Segmentation with SVM: Ambiguity Reduction and Suffix Capture
In this paper, we approach Vietnamese word segmentation as a binary classification by using the Support Vector Machine classifier.
A Pilot Study of Text-to-SQL Semantic Parsing for Vietnamese
We compare the two baselines with key configurations and find that: automatic Vietnamese word segmentation improves the parsing results of both baselines; the normalized pointwise mutual information (NPMI) score (Bouma, 2009) is useful for schema linking; latent syntactic features extracted from a neural dependency parser for Vietnamese also improve the results; and the monolingual language model PhoBERT for Vietnamese (Nguyen and Nguyen, 2020) helps produce higher performances than the recent best multilingual language model XLM-R (Conneau et al., 2020).
COVID-19 Named Entity Recognition for Vietnamese
The current COVID-19 pandemic has lead to the creation of many corpora that facilitate NLP research and downstream applications to help fight the pandemic.