Building and Incorporating Language Models for Persian Continuous Speech Recognition Systems

M. Bahrani, H. Sameti, N. Hafezi, H. Movasagh


Abstract
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.
Anthology ID:
L06-1014
Volume:
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)
Month:
May
Year:
2006
Address:
Genoa, Italy
Editors:
Nicoletta Calzolari, Khalid Choukri, Aldo Gangemi, Bente Maegaard, Joseph Mariani, Jan Odijk, Daniel Tapias
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2006/pdf/36_pdf.pdf
DOI:
Bibkey:
Cite (ACL):
M. Bahrani, H. Sameti, N. Hafezi, and H. Movasagh. 2006. Building and Incorporating Language Models for Persian Continuous Speech Recognition Systems. In Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06), Genoa, Italy. European Language Resources Association (ELRA).
Cite (Informal):
Building and Incorporating Language Models for Persian Continuous Speech Recognition Systems (Bahrani et al., LREC 2006)
Copy Citation:
PDF:
http://www.lrec-conf.org/proceedings/lrec2006/pdf/36_pdf.pdf