Pitch and Energy Trajectory Modelling in a Syllable Length Temporal Framework for Language Identification

Recent studies have indicated that language identity is encapsulated in a more complicated manner to that represented by short term acoustic features. In particular, trajectory information over syllable-like durations have shown significant promise. This study introduces a novel three-tiered language identification approach which incorporates this information as well as acoustic context in the form of broad syllabic events. Experimental results using the CallFriend database demonstrate the effectiveness of these systems at providing complementary information to a GMM based system