Development of an approach to language identification based on language-dependent phone recognition
Development of an approach to language identification based on language-dependent phone recognition
Automatic Prosodic Variations Modeling for Language and Dialect Discrimination
IEEE Transactions on Audio, Speech, and Language Processing
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part I
International Journal of Speech Technology
Semantic speech recognition in the Basque context Part I: cross-lingual approaches
International Journal of Speech Technology
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In this paper we propose a novel language identification system which utilizes fused phonotactic information. The phase spectrum of speech signals is used with the magnitude spectrum in order to obtain a more robust feature representation. Parallel Broad Phone-class Recognition followed by Language Model (PBPRLM) is used in order to remove the bias of the likelihood scores introduced by the size inequality of phone inventories in traditional PPRLM systems. The likelihood scores from the MFCC-based and group-delay-based PPRLM and PBPRLM systems are fused together by using a Gaussian Mixture Model. Furthermore, a pre-classification based on Kohonen's map is used in order to maintain the system robustness while handling a large number of target languages. Using this proposed novel system we achieve an EER of 6.7% on the 2005 NIST LRE, and a LID recognition rate of 83.9% on a 22-language task.