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Khmer Word Search: Challenges, Solutions, and Semantic-Aware Search

Autor: Buoy, Rina, Taing, Nguonly, Chenda, Sovisal

Search is one of the key functionalities in digital platforms and applications such as an electronic dictionary, a search engine, and an e-commerce platform. While the search function in some languages is trivial, Khmer word search is challenging giv

Externí odkaz: http://arxiv.org/abs/2112.08918

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Khmer Text Classification Using Word Embedding and Neural Networks

Autor: Buoy, Rina, Taing, Nguonly, Chenda, Sovisal

Text classification is one of the fundamental tasks in natural language processing to label an open-ended text and is useful for various applications such as sentiment analysis. In this paper, we discuss various classification approaches for Khmer te

Externí odkaz: http://arxiv.org/abs/2112.06748

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An End-to-End Khmer Optical Character Recognition using Sequence-to-Sequence with Attention

Autor: Buoy, Rina, Kor, Sokchea, Taing, Nguonly

This paper presents an end-to-end deep convolutional recurrent neural network solution for Khmer optical character recognition (OCR) task. The proposed solution uses a sequence-to-sequence (Seq2Seq) architecture with attention mechanism. The encoder

Externí odkaz: http://arxiv.org/abs/2106.10875

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Joint Khmer Word Segmentation and Part-of-Speech Tagging Using Deep Learning

Autor: Buoy, Rina, Taing, Nguonly, Kor, Sokchea

Khmer text is written from left to right with optional space. Space is not served as a word boundary but instead, it is used for readability or other functional purposes. Word segmentation is a prior step for downstream tasks such as part-of-speech (

Externí odkaz: http://arxiv.org/abs/2103.16801

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