Significance of CV transition and steady vowel regions for language identification

The present work explores the significance of the consonant-vowel (CV) transition and steady vowel (SV) regions for language identification (LID) task. The language-specific vocal tract information represented by Mel-frequency cepstral coefficients (MFCCs), extracted from the CV transition and steady vowel regions for LID task. The duration of CV transition and steady vowel regions are varied to analyze LID performance. The evidences obtained from the CV transition and steady vowel regions are combined to investigate the existence of complementary information in these two regions. The LID study carried out on 27 Indian languages from IITKGP-MLILSC speech database. The Gaussian mixture modelling (GMM) technique has been used for developing the language models. The average LID performances obtained by processing CV transition region and steady vowel regions are 70% and 71% respectively. In contemporary works, LID system has been developed by processing whole speech utterances, which provides 72% recognition accuracy.