What Are the Applications of Quantum NLP for Translation?

Applications of Quantum NLP for Translation


  • What Are the Applications of Quantum NLP for Translation?


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Frequently Asked Questions

QNLP (quantum-inspired neural models) for NLP differs significantly from existing NLP in that it employs the mathematical foundation of quantum theory to represent language aspects. The neural network then receives these quantum-theoretical properties as input. Further, since quantum mechanics notions have more detailed physical justifications, they are easier to understand when used to explain features.

The categorical distributional compositional (DisCoCat) model for natural language serves as the theoretical foundation for all QNLP techniques. DisCoCat encodes lexical meanings as quantum states and processes that may be implemented as quantum circuits in specialized hardware or simulators.

The key applications of QNLP include language production, text-to-voice processing, text analytics, automated speech, bioinformatics, etc.

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