an automated speech recognition system for phonological awareness of kindergarten students in filipino
Jazzmin R. Maranan · 2022
Phonological awareness is the ability to hear and attend to different units (e.g. syllables, onset and rime, and phonemes) of language. It is an essential aspect of a child’s learning development as it is a predictor of a child’s success in reading and spelling. The implemented phonological awareness system includes a Gaussian Mixture Model-Hidden Markov Model (GMM-HMM) based automated speech recognizer with pitch prosody-based data augmentation and vocal tract length normalization for children’s phonological awareness skill training and assessment. This study found that the use of pitch prosody-based augmentation is efficient in addressing the pitch and formant mismatch between the trained adult utterances and tested children’s utterances which entailed a WER of 15.08% or an increase in accuracy by 5.16% in comparison to the baseline system. The vocal tract length normalization (VTLN) adaptation did not show much significant improvement to the augmented system as the accuracy only increased by 0.12% or a WER of 14.96%.