Towards Quantum Language Models
This paper presents a new approach for building Language Models using the Quantum Probability Theory, a Quantum Language Model (QLM). It mainly shows that relying on this probability calculus it is possible to build stochastic models able to benefit from quantum correlations due to interference and entanglement. We extensively tested our approach showing its superior performances, both in terms of model perplexity and inserting it into an automatic speech recognition evaluation setting, when compared with state-of-the-art language modelling techniques.
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Tasks
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Decision MakingInformation RetrievalLanguage ModelingLanguage ModellingMachine TranslationPart-Of-Speech Taggingspeech-recognitionSpeech RecognitionSimilar Papers 제목 키워드 기반
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