MISPRONUNCIATION DETECTION IN NONNATIVE ENGLISH

Abstract

Detecting mispronunciations in non-native English speakers is a multifaceted process that requires a deep understanding of phonetics, phonology, and linguistic contrasts between the speaker's native language and English. This comprehensive analysis involves examining segmental features such as consonants and vowels, as well as suprasegmental features including stress, intonation, and rhythm. Phonetic transcription using the International Phonetic Alphabet (IPA) aids in comparing the pronunciation of words against their standard forms. Moreover, acoustic analysis through spectrograms and waveform analysis provides visual insights into speech sounds. Speech recognition technology complements this process by quantitatively evaluating pronunciation accuracy.