Mandarin digit recognition assisted by selective tone distinction

Continuous Mandarin digit recognition is an important function to provide a useful user interface for in-car applications. In this paper, as opposed to the conventional N-best rescoring, we propose a direct modification approach on the 1-best hypothesis of recognition results using selective tone distinction. Experiments were performed on noisy speech at SNRs of 20dB and 9dB. Over the baseline without using tone information, our proposal achieved error reductions of 24%~27% for both SNRs, which is significantly better than the error reduction of 10-best rescoring. Moreover, the relatively constant error reduction seen in wide-ranging SNR demonstrates the robustness of our proposal.