Automatic language recognition using acoustic features

Two language recognition algorithms are proposed and some experimental results are described. While many studies have been done concerning the speech recognition problem, few studies have addressed the language recognition task. The speech data used contains 20 languages: 16 sentences uttered twice by 4 males and 4 females. The duration of each sentence is about 8 seconds. The first algorithm is based on the standard vector quantization (VQ) technique. Every language is characterized by its own VQ codebook. The second algorithm is based on a single universal (common) VQ codebook for all languages, and its occurrence probability histograms. Every language is characterized by a histogram. The experiment results show that the recognition rates for the first and second algorithms were 65% and 80%, respectively, each using just 8 sentences of unknown speech (about 64 seconds).<<ETX>>

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