LP-TRAP: Linear predictive temporal patterns

Autoregressive modeling is applied for approximating the temporal evolution of spectral density in critical-band-sized sub-bands of a segment of speech signal. The generalized autocorrelation linear predictive technique allows for a compromise between fitting the peaks and the troughs of the Hilbert envelope of the signal in the sub-band. The cosine transform coefficients of the approximated sub-band envelopes, computed recursively from the all-pole polynomials, are used as inputs to a TRAP-based speech recognition system and are shown to improve recognition accuracy.


Publié dans:
International Conference on Spoken Language Processing (ICSLP)
Année
2004
Mots-clefs:
Note:
IDIAP RR 04-59
Laboratoires:




 Notice créée le 2006-03-10, modifiée le 2019-12-05

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