Automatic language identification based on Gaussian mixture model and universal background model

Citations Over Time

Abstract

When compared with speech technologies in speech processing, automatic language identification is a relatively new yet difficult problem. In this paper, a language identification algorithm is provided and some experiments are conducted using OGI multi-language telephone speech corpus (OGI-TS). Then experiments results are described. It is shown that GMM-UBM is another efficient method to language identification problems.

Related Papers

• → Development of an approach to automatic language identification based on phone recognition(1996)24 cited
• → Automatic language identification based on Gaussian mixture model and universal background model(2003)1 cited
• The model for identification of a natural language of the text(2011)
• → Toward new language adaptation for language identification(1997)4 cited
• Robust Techniques Of Language Modeling For Spoken Language Identification(2009)