This work explores the possibilities to use quantum computers and quantum based language models for machine translation. Precise translation requires vast expertise and knowledge of various languages, thus machine translationis still far from superseding humans. Quantum computers could improve machine translation due to their high computational power, as they benefit from properties such as superposition and entanglement to process data faster and in parallel. We focused our work on the DIStributional COmpositional CATegorical (DisCoCat) semantics and its python toolbox DisCoPy developed by [1]. We built and transformed simple, complex, and negative English and Spanish sentences to DisCoCat diagrams. Those diagrams are then used as input to quantum circuits, allowing us to perform calculations in NISQ devices providedby IBMQ. The calculations show that a quantum computer can understand the meaning of simple and complex sentences in different languages, and this is the first step to perform translation with Quantum Computers. In addition, we worked on preserving sentence meaning by measuring the cosine similarity between two vectorised sentences and obtained sentence similarities scores of 95%.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:su-196602 |
| Date | January 2021 |
| Creators | Vicente Nieto, Irene |
| Publisher | Stockholms universitet, Fysikum |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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