Despite growing interest in smart-homes, semantically annotated large voice command corpora for Natural Language development (NLU) are scarce, especially for languages other than English. In this paper, we present an approach to generate customizable synthetic corpora of semantically-annotated French commands for a smart-home. This corpus was used to train three NLU models-a triangular CRF, an attention-based RNN and the Rasa framework-evaluated using a small corpus of real users interacting with a smart home. While the attention model performs best on another large French dataset, on the small smart home corpus the models vary performance across to intent, slot and slot value classification. To the best of our knowledge, no other French corpus of semantically annotated voice commands is currently publicly available
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