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A Language Model for Intelligent Speech Recognition of Power Dispatching

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Published:02 October 2021Publication History

ABSTRACT

The accuracy of power dispatching speech recognition system is related to the effect of language model. In order to improve the accuracy of power dispatching speech recognition, this paper proposes a class label language model based on double dictionaries (general dictionary and power dispatching professional word dictionary). The model improves the n-gram language model with adding class label information, so as to improve the accuracy of power dispatching speech recognition. In addition, the joint system (the joint system of word segmentation and part of Speech Tagging based on double dictionaries) is used to preprocess the corpus information, which will improve the adaptability of class label language model based on double dictionary to power dispatching language. Finally, the class label language model is trained on the collected training corpus of power dispatching instructions. The word error rate of the power dispatching language recognition system using the class label language model based on double dictionaries in the test set are only 4.14%.

References

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              cover image ACM Other conferences
              ACM TURC '21: Proceedings of the ACM Turing Award Celebration Conference - China
              July 2021
              284 pages
              ISBN:9781450385671
              DOI:10.1145/3472634

              Copyright © 2021 ACM

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              Publication History

              • Published: 2 October 2021

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