IEEE Access, Volume (9), No (1), Year (2021-1) , Pages (130434-130448)

Title : ( Application of Quantum Natural Language Processing for Language Translation )

Authors: MINA ABBASZADE , VAHID SALARI , SEYED SHAHIN MOUSAVI , Mariam Zomorodi-Moghadam , XUJUAN ZHOU ,

Citation: BibTeX | EndNote

Abstract

In this paper, we develop compositional vector-based semantics of positive transitive sentences using quantum natural language processing (Q-NLP) to compare the parametrized quantum circuits of two synonymous simple sentences in English and Persian. We propose a protocol based on quantum long short-term memory (Q-LSTM) for Q-NLP to perform various tasks in general but specifically for translating a sentence from English to Persian. Then, we generalize our method to use quantum circuits of sentences as an input for the Q-LSTM cell. This enables us to translate sentences in different languages. Our work paves the way toward representing quantum neural machine translation, which may demonstrate quadratic speedup and converge faster or reaches a better accuracy over classical methods.

Keywords

, Q-NLP, DisCoCat diagrams, ZX-calculus, quantum circuits, Q-LSTM
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@article{paperid:1088521,
author = {MINA ABBASZADE and VAHID SALARI and SEYED SHAHIN MOUSAVI and Zomorodi-Moghadam, Mariam and XUJUAN ZHOU},
title = {Application of Quantum Natural Language Processing for Language Translation},
journal = {IEEE Access},
year = {2021},
volume = {9},
number = {1},
month = {January},
issn = {2169-3536},
pages = {130434--130448},
numpages = {14},
keywords = {Q-NLP; DisCoCat diagrams; ZX-calculus; quantum circuits; Q-LSTM},
}

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%0 Journal Article
%T Application of Quantum Natural Language Processing for Language Translation
%A MINA ABBASZADE
%A VAHID SALARI
%A SEYED SHAHIN MOUSAVI
%A Zomorodi-Moghadam, Mariam
%A XUJUAN ZHOU
%J IEEE Access
%@ 2169-3536
%D 2021

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