Publicado en 3C Tecnología – Volume 13 Issue 1 (Ed. 45)

Autores

• Shaohua Jiang


• Zheng Chen*

Resumen

Abstract

In modern linguistic research, the application of Artificial Intelligence has led the field and provided powerful tools and prospects for linguists. LSTM is used for extracting character features, joint vector representation and constructing text generation models and generating natural language text. LSTM is involved in the design of speech recognition network to process the input speech signals for generators and discriminators to improve the accuracy of speech recognition. By continuously optimizing the training objectives, the translation system will more accurately translate text from one language to another, thus facilitating cross-cultural communication. Through the application of artificial intelligence, the F1 value has been improved by 3.9% compared with the previous value, and the cumulative variance contribution rate of the five factors is more than 60%, with all subloadings reaching 0.4 or more. Artificial intelligence will promote the development of the field of linguistics, improve research efficiency and accuracy, and promote the innovation of language technology.

Artículo

Palabras clave

Keywords

Artificial intelligence; LSTM; joint vector; speech recognition; F1 value

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