Phoneme Recognizers followed by Language Modeling (PRLM) have consistently yielded top performance in language identification (LID) task. Parallel ordering of PRLMs (PPRLM) improves performance even more. Since tokenizer is the most important part of LID system the high quality phoneme recognizer is employed. Two different multilingual databases for training phoneme recognizers are compared and the amount of sufficient training data is studied. Reported results are on data from NIST 2003 LID evaluation. Our four PRLM systems have Equal Error Rate (EER) of 2.4% on 12 languages task. This result compares favorably to the best known result from this task.
Cite as: Matejka, P., Schwarz, P., Cernocký, J., Chytil, P. (2005) Phonotactic language identification using high quality phoneme recognition. Proc. Interspeech 2005, 2237-2240, doi: 10.21437/Interspeech.2005-708
@inproceedings{matejka05_interspeech,
author={Pavel Matejka and Petr Schwarz and Jan Cernocký and Pavel Chytil},
title={{Phonotactic language identification using high quality phoneme recognition}},
year=2005,
booktitle={Proc. Interspeech 2005},
pages={2237--2240},
doi={10.21437/Interspeech.2005-708}
}