An automatic language identification system

Abstract
An automatic language identification system which makes use of several language specific features is described. The system concurrently utilizes features associated with two methodologies, the hidden Markov model, (HMM) and language-specific pitch contours. Experimental results show that transition probabilities and pitch contours show differences between the languages. However, each of the described criteria will not give in every case a definitive answer, but will lead in the correct direction. Therefore, a voting classifier should be used to combine the results from each of the criteria.

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