In this paper we propose an automatic approach for foreign accent identification. Knowledge of the speaker's origin allows to adapt acoustic models for non-native speech recognition. In this study, we use a statistical approach based on prosodic parameters. This approach relies on the fact that prosody is different between languages, and has been done within the framework of the HIWIRE (Human Input that Works In Real Environments) European project. The corpus is composed of English sentences pronounced by French, Italian, Greek and Spanish speakers. Results obtained with duration and energy are promising for foreign accent identification: 67.1% correct L1 identification with duration and 68.6% with energy. These two parameters combined with MFCC achieve a 87.1% correct foreign accent identification rate.