FreeTxt-Vi: A Benchmarked Vietnamese-English Toolkit for Segmentation, Sentiment, and Summarisation

Abstract

FreeTxt-Vi is a free and open-source web-based toolkit for creating and analysing bilingual Vietnamese–English text collections. Positioned at the intersection of corpus linguistics and natural language processing (NLP), it enables users to build, explore, and interpret free-text data without requiring programming expertise. The system combines established corpus analysis features such as concordancing, keyword analysis, word relation exploration, and interactive visualisation with modern transformer-based NLP components for sentiment analysis and summarisation. A key contribution of this work is the design of a unified bilingual NLP pipeline that integrates a hybrid VnCoreNLP + Byte Pair Encoding (BPE) segmentation strategy, a fine-tuned TabularisAI sentiment classifier, and a fine-tuned Qwen2.5 model for abstractive summarisation. Unlike existing text analysis platforms, FreeTxt-Vi is evaluated as a set of language processing components. We conduct a three-part evaluation covering segmentation, sentiment analysis, and summarisation, and demonstrate that our approach achieves competitive or superior performance compared to widely used baselines in both Vietnamese and English. By reducing technical barriers to multilingual text analysis, FreeTxt-Vi supports reproducible research and promotes the development of language resources for Vietnamese, a widely spoken but underrepresented language in NLP. The toolkit is applicable to a wide range of domains, including education, digital humanities, cultural heritage, and the social sciences, where qualitative text data are common but often difficult to process at scale.

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