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TRAP-TANDEM: data-driven extraction of temporal features from speech

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1 Author(s)
Hermansky, H. ; Inst. Dalle Molle d''Intelligence Artificielle Perceptive, Martigny, Switzerland

Conventional features in automatic recognition of speech describe the instantaneous shape of a short-term spectrum of speech. The TRAP-TANDEM features describe the likelihood of sub-word classes at a given time instant, derived from temporal trajectories of band-limited spectral densities in the vicinity of the given instant. The paper presents some rationale behind the data-driven TRAP-TANDEM approach, briefly describes the technique, points to relevant publications and summarizes results achieved so far.

Published in:

Automatic Speech Recognition and Understanding, 2003. ASRU '03. 2003 IEEE Workshop on

Date of Conference:

30 Nov.-3 Dec. 2003