Automatic recognition of the language of spontaneous speech is a difficult problem that has been studied for years. This article provides a brief introduction to the general topic and an examination of a specific implementation that has already achieved a level of performance adequate for real applications. A detailed performance analysis provides a comparison of various techniques in terms of recognition accuracy and computational costs. Error rates of 5% and systems running eight-times real time have already been achieved. Issues of training on learning data and evaluation databases are addressed.
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