Enhanced Speech Recognition via A TensorFlow-Powered Lip Reading Model for Educational Applications

Speech Recognition is a widely practiced technology and has many applications in the academic domain and beyond.In educational research, AI-based speech recognition serves different purposes such as analysis of students' team discussions, and classroom discourses, as well as assisting students with disabilities and hearing problems with transcriptions.However auditory speech recognition presents some challenges like environmental noise, poor audio quality, or even speaker identification in discourse analysis.This paper proposes an innovative approach to address these challenges by introducing a cutting-edge AI model for lip reading using Tensorflow.Our proposed model eliminates the need for auditory inputs in speech recognition, by utilizing artificial intelligence to analyze speech through visual cues of lip reading, also known as Visual Speech Recognition (VSR).The application of this novel method can significantly impact pedagogical practices.By providing a real-time transcription of speech from lip-reading into text, it offers an advanced assistive learning tool for students with disabilities and greatly enhances knowledge accessibility.