Advances in regional accent clustering in Swedish

QC 20100630
The regional pronunciation variation in Swedish is analysed on a large database. Statistics over each phoneme and for each region of Sweden are computed using the EM algorithm in a hidden Markov model framework to overcome the difficulties of transcribing the whole set of data at the phonetic level. The model representations obtained this way are compared using a distance measure in the space spanned by the model parameters, and hierarchical clustering. The regional variants of each phoneme may group with those of any other phoneme, on the basis of their acoustic properties. The log likelihood of the data given the model is shown to display interesting properties regarding the choice of number of clusters, given a particular level of details. Discriminative analysis is used to find the parameters that most contribute to the separation between groups, adding an interpretative value to the discussion. Finally a number of examples are given on some of the phenomena that are revealed by examining the clustering tree.

Ingår i:Proceedings of European Conference on Speech Communication and Technology (Eurospeech), s. 2841-2844

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