Cross-linguistic rhythm analysis of Mising and Assamese

Abstract

The objective of the current study is to explore a quantitative frequency domain technique to evaluate rhythm in spontaneous speech data of 19 native speakers of Mising and Assamese, two low-resourced languages spoken in Assam, North-East India. The concept of analyzing speech rhythm using amplitude modulation (AM) low-frequency (LF) spectrum, also known as rhythm formant analysis (RFA), is initially put forth by Gibbon and Li [ 17 ]. We propose three features from rhythm formants of the LF spectrum and also explore discrete cosine transform (DCT)–based characterization of the retrieved LF spectrum. We aim to distinguish the rhythm of Assamese and two Mising dialects, namely Pagro and Delu, with the aid of machine learning techniques fed with the derived features as input. We have observed that the features are efficient in classifying Assamese vs Pagro and Assamese vs Delu with an accuracy of 92.73% and 91.15%, respectively. The experimental analysis further reveals that Assamese is rhythmically closer to Delu than Pagro.