Automatic classification of accent and dialect type: results from southern Swedish

This paper is about automatic classification of dialect and accent type in Swedish. We used disyllabic words from the speech material of the Swedia 2000 dialect project in order to build a statistical prediction model. The model uses different parameters extracted from F0 contours of the words. Classification of dialect is performed for the features 'province' and 'village', whereas classification of accent is performed for the feature 'type'. The best results for province, village and accent type are 30.3%, 15.7% and 85.4% correct predictions, respectively. This shows that the categories of province and village are too specific to use for a prediction model based on these F0 parameters, whereas it is possible to predict accent type with some accuracy even across dialects.