Hamed Movasagh

Also published as: H. Movasagh


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Building and Incorporating Language Models for Persian Continuous Speech Recognition Systems
M. Bahrani | H. Sameti | N. Hafezi | H. Movasagh
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)

In this paper building statistical language models for Persian language using a corpus and incorporating them in Persian continuous speech recognition (CSR) system are described. We used Persian Text Corpus for building the language models. First we preprocessed the texts of corpus by correcting the different orthography of words. Also, the number of POS tags was decreased by clustering POS tags manually. Then we extracted word based monogram and POS-based bigram and trigram language models from the corpus. We also present the procedure of incorporating language models in a Persian CSR system. By using the language models 27.4% reduction in word error rate was achieved in the best case.