An Optimal Method for Speech Recognition Based on Neural Network  

作　　者：Mohamad Khairi Ishak DagØivind Madsen Fahad Ahmed Al-Zahrani 

机构地区：[1]School of Electrical and Electronic Engineering,Universiti Sains Malaysia,Nibong Tebal,14300,Malaysia [2]University of South-Eastern Norway,Bredalsveien 14,3511,Hønefoss,Norway [3]Computer Engineering Department,Umm Al-Qura University,Mecca,24381,Saudi Arabia

出　　处：《Intelligent Automation & Soft Computing》2023年第5期1951-1961,共11页智能自动化与软计算（英文）

基　　金：the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code:(22UQU4170008DSR06).

摘　　要：Natural language processing technologies have become more widely available in recent years,making them more useful in everyday situations.Machine learning systems that employ accessible datasets and corporate work to serve the whole spectrum of problems addressed in computational linguistics have lately yielded a number of promising breakthroughs.These methods were particularly advantageous for regional languages,as they were provided with cut-ting-edge language processing tools as soon as the requisite corporate information was generated.The bulk of modern people are unconcerned about the importance of reading.Reading aloud,on the other hand,is an effective technique for nour-ishing feelings as well as a necessary skill in the learning process.This paper pro-posed a novel approach for speech recognition based on neural networks.The attention mechanism isfirst utilized to determine the speech accuracy andfluency assessments,with the spectrum map as the feature extraction input.To increase phoneme identification accuracy,reading precision,for example,employs a new type of deep speech.It makes use of the exportchapter tool,which provides a corpus,as well as the TensorFlow framework in the experimental setting.The experimentalfindings reveal that the suggested model can more effectively assess spoken speech accuracy and readingfluency than the old model,and its evalua-tion model’s score outcomes are more accurate.

关 键 词：Machine learning neural networks speech recognition signal processing learning process fluency and accuracy 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]