A comprehensive Turkish accent/dialect recognition system using acoustic perceptual formants

Abstract

Accent or dialect is one of the hot topics of emerging technology in speech processing. In an audio recording, extracting accent clues from a speech signal can help investigators to have an idea about where speaker is from. It is mostly used for detecting regional origin/ethnicity of speakers in real-time surveillance systems as well as demographic researches about changes in human sounds by geography. In this work, Turkish language accent analysis was performed using formant frequencies (F1, F2 and F3) of vowels. We divided our work into two approaches which are statistical and classification. In both of them, evaluations were done by splitting Turkey’s map in to 2 and 3 dialect regions virtually. Totally 112 monolingual university students (72 males, 40 females) have uttered 103 meaningful Turkish syllables. Because formant frequencies can vary depending on genders, males and females were evaluated separately in both statistical and classification analysis. The result surprisingly showed that especially the isolated vowel ‘e’ is able to classify a male speaker which was pre-known to be from Mediterranean or Eastern Anatolia regions with an accuracy of 90% using KNN classifier.