A voicing feature is used in concatenation to MFCC features to increase the performance of digit recognition at both low and high SNRs. The problem of noise robust extraction of the voicing feature is solved by using the glottal electromagnetic sensor (GEMS). The GEMS device provides reliable voicing information at all SNRs and noise environments. It is shown that although the voicing feature increases the performance for the clean speech case, the relative improvement for the noisy case is significantly higher for a digit recognition task. Our results indicate that the GEMS device can solve the fundamental problem of extracting reliable voicing information in noisy environments.