Quantum Natural Language Generation on Near-Term Devices

TL;DR

This paper presents a hybrid quantum-classical algorithm for sentence generation that leverages near-term quantum devices, demonstrating successful implementation on simulated and real hardware, and extending to music generation.

Contribution

It introduces a novel quantum-inspired algorithm for natural language and music generation, bridging quantum computing and NLP at the hardware's current capabilities.

Findings

Successful sentence generation on quantum hardware

Algorithm applicable to music generation

Demonstrates feasibility of quantum NLP tasks

Abstract

The emergence of noisy medium-scale quantum devices has led to proof-of-concept applications for quantum computing in various domains. Examples include Natural Language Processing (NLP) where sentence classification experiments have been carried out, as well as procedural generation, where tasks such as geopolitical map creation, and image manipulation have been performed. We explore applications at the intersection of these two areas by designing a hybrid quantum-classical algorithm for sentence generation. Our algorithm is based on the well-known simulated annealing technique for combinatorial optimisation. An implementation is provided and used to demonstrate successful sentence generation on both simulated and real quantum hardware. A variant of our algorithm can also be used for music generation. This paper aims to be self-contained, introducing all the necessary background on NLP and quantum computing along the way.