Phonetic differences for dialect clustering
Ahmed Omer, Marcos Zampieri, Michael Oakes · 2018
In this paper we investigate differences and similarities between dialects using unsupervised learning. We used a binary phonetic representation to cluster utterances from different Arabic and English dialects. This phonetic representation aims to capture phonetic patterns such as vowel and consonant length. We tested this representation on an Arabic dataset containing utterances from speakers of four dialects: Egyptian, Gulf, Levantine, and North African. We validate our approach on an English dataset containing utterances from speakers from Bradford, Cardiff, Dublin, and Liverpool.