In this paper we propose an automatic approach to foreign accent identification. Knowing the speaker origin could allow to adapt the 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 so between accents. This work is done in the framework of the HIWIRE (Human Input that Works In Real Environment) 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 : 68.6% with energy and 67.1% with duration. These two parameters combined with MFCC achieve a 87.1% correct foreign accent identification rate.