Behavioral synchronization between speech and finger tapping provides a novel approach to the improvement of speech recognition accuracy. We combine a sequence of finger tapping timings recorded alongside an utterance using two distinct methods: in the first method, HMM state transition probabilities at the word boundaries are controlled by the timing of the finger tapping; in the second, the probability (relative frequency) of the finger tapping is used as a 'feature' and combined with MFCC in a HMM recognition system. We evaluate these methods through connected digit recognition under different noise conditions (AURORA-2J) and LVCSR tasks. Leveraging the synchrony between speech and finger tapping provides a 46 % relative improvement and a 1 % absolute improvement in connected digit recognition experiments and LVCSR experiments, respectively.