Speech recognition with matrix-MCE based two-dimension-cepstrum in cars

This study proposes matrix-MCE (MMCE) to reduce the influence of noises. Background noises usually degrade the performance of speech recognition. MMCE can efficiently minimize the classification error of two-dimension-cepstrum (TDC). Then the template matching employs the Gaussian-mixture-model (GMM). To evaluate the performance, the speech data used for our experiments are a set of isolated Mandarin digits. Experimental results indicate that MMCE-based TDC is very robust in the noisy environments.