Journal Article

Cross-Lingual Short-Text Semantic Similarity for Kannada–English Language Pair

S N, Muralikrishna, Holla, Raghurama, Ganiga, Raghavendra, N, Harivinod

2024

Overview

Analyzing the semantic similarity of cross-lingual texts is a crucial part of natural language processing (NLP). The computation of semantic similarity is essential for a variety of tasks such as evaluating machine translation systems, quality checking human translation, information retrieval, plagiarism checks, etc. In this paper, we propose a method for measuring the semantic similarity of Kannada–English sentence pairs that uses embedding space alignment, lexical decomposition, word order, and a convolutional neural network. The proposed method achieves a maximum correlation of 83% with human annotations. Experiments on semantic matching and retrieval tasks resulted in promising results in terms of precision and recall.

• Publisher: MDPI AG
• Subject: Algorithms / Analysis / Annotations / Approximation / Artificial neural networks / Computational linguistics / cross-lingual semantic similarity / English language / Graph representations / Information retrieval / Kannada monolingual embedding / Language / Language processing / lexical decomposition / Machine translation / Measurement methods / Methods / Multilingualism / Natural language interfaces / Natural language processing / Neural networks / Regression analysis / Semantics / sentence similarity / short-text semantic similarity / Similarity / word embedding