Constructing an AI-Assisted Pronunciation Correction Tool Using Speech Recognition and Phonetic Analysis for ELL

This research proposes the development of an innovative AI-assisted Pronunciation Correction Tool designed to enhance the English language learning experience for nonnative speakers. The tool combines advanced speech recognition technology with detailed phonetic analysis to provide personalized feedback on pronunciation errors. The system employs state-of-the-art automatic speech recognition (ASR) algorithms to accurately transcribe spoken language input. This transcription is then compared with the target pronunciation using sophisticated phonetic analysis techniques. The tool leverages a comprehensive phonetic database to identify specific phonemes, intonation patterns, and stress points that contribute to pronunciation challenges for English Language Learners (ELL). To ensure adaptability and effectiveness, the tool incorporates machine learning models that continuously evolve based on user interactions. The AI model learns from user-specific pronunciation patterns, adapting feedback to address individual strengths and weaknesses. Users receive instant visual and auditory cues highlighting areas of improvement, along with detailed suggestions for correction. The tool also offers interactive exercises and practice modules to reinforce learning and encourage consistent improvement. The proposed AI-assisted Pronunciation Correction Tool has the potential to revolutionize language learning. The robust 88% accuracy in evaluating intonation and stress patterns is crucial for achieving the research goal of providing comprehensive feedback on speech dynamics.