Reconocimiento automático de voz aplicado a la mejora en el proceso de aprendizaje de lectura en nivel escolar

Abstract

This article conducts the study of the algorithms and methods used for automatic speech recognition. The importance of its application lies in improving the learning process taking into account characteristics such as pronunciation, communication, and linguistic skills in improving the accuracy and good use of speech. A search was carried out for the different studies related to the objective of analyzing the most used algorithm and the method that complements it to find the most relevant and inconvenient characteristics in its use. Thus, one of the most commonly used algorithms was found to be DNN (deep neural networks) and HMM (hidden Markov model). From this review, we observed that the use of speech recognition for learning has been experienced from an early age in children, adolescents, and adults with relevant results, being one of the main drawbacks to its operation, noise