Mel frequency cepstral coefficients based similar albanian phonemes recognition

Abstract

In Albanian language there are several phonemes that are similar in pronunciation like /q/ - /ç/, /rr/ - /r/, /th/ - /dh/ and /gj/ - /xh/. These phonemes are difficult to distinguish by human ear even for native speaking Albanians from different regions. The task becomes more challenging for automated speech systems, recognizing and classifying Albanian words and language due to the similar sounding phonemes. This paper proposes to use Mel Frequency Cepstral Coefficients (MFCC) based features to distinguish these phonemes correctly. The three layers back propagation neural network is used for classification. The experiments are performed on speech signals that are collected from different male and female native speakers. The speaker independent tests are performed for analyzing the performance of the classification. The obtained results show that the serial MFCC features can be used to classify the very similar speech phonemes with higher accuracy.