This paper emphasizes the importance of the question of word-order variation in connectionist language modeling. More precisely, it investigates whether recurrent networks can integrate various linguistic constraints to process variable word-order languages. This paper reports three experiments on the understanding of spoken French that suggest that recurrent architectures could apply to the understanding of variable spoken languages.