JOURNAL ARTICLE

Turkish Large Vocabulary Continuous Speech Recognition by using limited audio corpus

Abstract

In this paper, the recognition performances of several methodologies proposed in the context of Turkish Large Vocabulary Continuous Speech Recognition are retrieved by using a limited audio corpus. Word based, stem based, stem-ending based, and morph based language models are utilized with different n-gram orders. Word based and stem-ending based language models are extended by using several approaches. Also, a hybrid language model which is based on word based and stem-ending based language models is proposed. Word based language model is observed to outperform sub-word language models when limited audio corpus is used.

Keywords:
Computer science Vocabulary Language model Speech recognition Word (group theory) Turkish Natural language processing Artificial intelligence Cache language model Context (archaeology) Audio mining Acoustic model Speech processing Linguistics Natural language Universal Networking Language

Metrics

4
Cited By
0.00
FWCI (Field Weighted Citation Impact)
5
Refs
0.08
Citation Normalized Percentile
Is in top 1%
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Citation History

Topics

Speech Recognition and Synthesis
Physical Sciences →  Computer Science →  Artificial Intelligence
Music and Audio Processing
Physical Sciences →  Computer Science →  Signal Processing
Speech and Audio Processing
Physical Sciences →  Computer Science →  Signal Processing
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