Dialect Identification Using Tonal and Spectral Features in Two Dialects of Ao

Abstract

Ao is an under-resourced Tibeto-Burman tone language spoken in Nagaland, India, with three lexical tones, namely, high, mid and low. There are three dialects of the language namely, Chungli, Mongsen and Changki, differing in tone assignment in lexical words. This work investigates if the idiosyncratic tone assignment in the Ao dialects can be utilized for dialect identification of two Ao dialects, namely, Changki and Mongsen. A perception test confirmed that Ao speakers identified the two dialects based on their dialect-specific tone assignment. To confirm that tone is the primary cue in dialect identification, F0 was neutralized in the speech data before subjecting them to a Gaussian Mixture Model (GMM) based dialect identification system. The low dialect recognition accuracy confirmed the significance of tones in Ao dialect identification. Finally, a GMM-based dialect identification system was built with tonal and spectral features, resulting in better dialect recognition accuracy.