Formant weighted cepstral feature for LSP-based speech recognition

نویسندگان

  • Ho Young Hur
  • Hyung Soon Kim
چکیده

In this paper, we propose a formant weighted cepstral feature for LSP-based speech recognition system. The proposed weighting scheme is based on the well-known property of LSPs that the speech spectrum has a peak when adjacent LSFs come close. By applying this scheme to pseudo-cepstrum (PCEP) conversion process [1], we can obtain formant weighted or peak enhanced cepstral feature. Results of speech recognition experiments using QCELP coder output show that the proposed feature set outperforms the conventional features such as LSP or PCEP. Moreover its performance also exceeds that of unquantized LPC cepstrum.

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تاریخ انتشار 2001