Application of Voice Recognition Technology in Diary Applications

Abstract

Traditional diary applications mainly rely on keyboard input, which makes it difficult for users to quickly record their thoughts and feelings when their emotions fluctuate violently. This paper uses voice recognition technology to innovate the recording method of diary applications and optimize the user experience. This paper uses multiple voice data sets for training to ensure the accuracy and generalization ability of the model; a voice recognition method is constructed based on a one-dimensional convolutional neural network (1D CNN), which can accurately extract features from continuous voices and achieve high-quality voice transcription. The AM and NLP technology are introduced to further process the recognized text and improve the accuracy of its grammar, logic and emotional expression. Experimental results show that the method based on 1D CNN has an accuracy rate, word missing rate and vocabulary coverage of 94.61%, 3.17% and 93.11% respectively. Regarding time efficiency, the average input time of 1D CNN is 6.46 seconds. Voice recognition technology has great potential in diary applications. It can significantly improve recording efficiency and user experience, making diary content more authentic, fluent and personalized.