Perceptual benchmarks for automatic language identification

There has been renewed interest in the field of automatic language identification over the past two years. The advent of a public-domain ten-language corpus of telephone speech has made the evaluation of different approaches to automatic language identification feasible. In an effort to provide benchmarks for evaluating machine performance, we conducted perceptual experiments on 1-, 2-, 4- and 6-second excerpts of telephone speech excised from spontaneous speech utterances in this corpus. The subject population consisted of 10 native speakers of English and 2 speakers from each of the remaining 9 languages. Statistical analyses of our results indicate that duration of the excerpt, familiarity with the language, and number of languages known are important factors affecting a subject´s performance on the identification task