Application of quantum natural language processing for language translation
Authors:
- Mina Abbaszade,
- Vahid Salari,
- Seyed Shahin Mousavi,
- Mariam Zomorodi,
- Xujuan Zhou
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.
- Record ID
- CUT4571659c66354e98b379548437cb9396
- Publication categories
- ;
- Author
- Journal series
- IEEE Access, ISSN 2169-3536
- Issue year
- 2021
- Vol
- 9
- Pages
- 130434-130448
- Other elements of collation
- rys.; schem.; tab.; Bibliografia (na s.) - 130447-130448; Bibliografia (liczba pozycji) - 41; Oznaczenie streszczenia - Abstr.; Numeracja w czasopiśmie - Vol. 9
- Keywords in English
- Q-NLP, DisCoCat diagrams, ZX-calculus, quantum circuits, Q-LSTM
- DOI
- DOI:10.1109/ACCESS.2021.3108768 Opening in a new tab
- URL
- https://ieeexplore.ieee.org/abstract/document/9525075 Opening in a new tab
- Language
- eng (en) English
- License
- Score (nominal)
- 100
- Additional fields
- Indeksowana w: Web of Science, Scopus
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUT4571659c66354e98b379548437cb9396/
- URN
urn:pkr-prod:CUT4571659c66354e98b379548437cb9396
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.