An integrated spoken language recognition system using support vector machines

Abstract

An automatic Language Identification (LID) is a system designed to recognize a language from a given spoken utterance. The spoken utterances are classified according to the pre-defined set of languages. In this paper a LID system is designed for two different languages namely English and French. The classification of an audio sample is done by extracting Mel frequency cepstral coefficients (MFCCs) and putting them on support vector machines with radial basis function kernel. The proposed framework is speaker-independent. This scheme was tested on a database of multi-lingual speech samples. The language identification accuracy is found to be 92% for French and 88% for English.