Speech recognition using a throat microphone is studied. Good signal-to-noise ratios are obtained from throat microphones even under heavy environmental noise; however, the spectrum is much different from that of an acoustic microphone and varies according to position. In order to clarify the effect of mounting position, we first measured the spectral distance between close-talk and throat microphones. Secondly, we gathered a medium-sized corpus of training data by using a throat microphone mounted at a suitable position and utilized them to improve speech recognition accuracy. When applying knowledge distillation (KD) to the DNN-HMM with this training data in a quiet environment, throat microphone speech recognition achieved a performance close to that of close-talk microphones.