In continuation of our previous work on using an air-and-boneconductive microphone for speech enhancement, in this paper we propose a graphical model based approach to estimating the clean speech signal given the noisy observations in the air sensor. We also show how the same model can be used as a speech/non-speech classifier. With the aid of MOS (mean opinion score) tests we show, that the performance of the proposed model is better in comparison to our previously proposed direct filtering algorithm.