LSP weighting functions based on spectral sensitivity and mel-frequency warping for speech recognition in digital communication

  • Authors:

  • R. Haeb-Umbach

  • Affiliations:

  • Dept. of Electr. Eng., Korea Adv. Inst. of Sci. & Technol., Seoul, South Korea

  • Venue:
  • ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01
  • Year:
  • 1999

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Abstract

In digital communication networks, a speech recognition system extracts feature parameters after reconstructing speech signals. In this paper, we consider a useful approach of incorporating speech coding parameters into a speech recognizer. Most speech coders employ line spectrum pairs (LSPs) to represent spectral parameters. We introduce weighted distance measures to improve the recognition performance of an LSP-based speech recognizer. Experiments on speaker-independent connected-digit recognition showed that weighted distance measures provide better recognition accuracy than unweighted distance measures do. Compared with a conventional method employing mel-frequency cepstral coefficients, the proposed method achieved higher performance in terms of a recognition accuracy.