  This paper presents a vowel-based dialect identification system for
Meeteilon. For this work, a vowel dataset is created by using Meeteilon Speech
Corpora available at Linguistic Data Consortium for Indian Languages (LDC-IL).
Spectral features such as formant frequencies (F1, F1 and F3) and prosodic
features such as pitch (F0), energy, intensity and segment duration values are
extracted from monophthong vowel sounds. Random forest classifier, a decision
tree-based ensemble algorithm is used for classification of three major
dialects of Meeteilon namely, Imphal, Kakching and Sekmai. Model has shown an
average dialect identification performance in terms of accuracy of around
61.57%. The role of spectral and prosodic features are found to be significant
in Meeteilon dialect classification.
