Journal article Open Access
Hussein Seid,; Mitiku Tamirat
Abstract—this paper analyzes acoustic characteristics of nasal sounds of Kambaata language at their place of
articulation by using autoregressive moving average(ARMA) model. The ARMA model is an extension of
Linear Predictive Coding (LPC) model, which incorporatethe zeros of the transfer function of vocal tract coupled
with nasal cavity. Since nasal sound production involves the coupling of nasal cavity, so it can be modeled by ARMA
process. Sounds of minimal or nearly minimal pair words, containing singleton or geminated nasal phoneme at the
initial, medial or final positions were recorded while read by five male and five female native speakers is collected.
Formant and ant-formant frequencies of the collected speech has been extracted and analyzed by using one-way
ANOVA test to analyze the differences of nasal sounds. The overall duration measurement is also used to
characterize the acoustic nature of nasals. It was observed that Kambaata geminated nasals are found to have
statistically longer in overall duration than their singleton conjugates for both females and males in all word positions
(initial, medial and final). Anti-formant frequencies are found to have statistically significant difference for both
female and males at all positions of the target phoneme. In future, it can be extended for noisy and live environments.