Speech synthesis techniques have already reached a high level of naturalness. However, they are often evaluated on text reading tasks. New applications will request for conversational speech instead and disfluencies are crucial in such a style. The present paper presents a system to predict filled pauses and synthesise them. Objective results show that they can be inserted with 96% precision and 58% recall. Perceptual results even shown that its insertion increases naturalness of synthetic speech.