Trap-tandem: Data-driven Extraction of Temporal Features from Speech
نویسنده
چکیده
Conventional features in automatic recognition of speech describe instantaneous shape of a short-term spectrum of speech. The TRAP-TANDEM features describe 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.
منابع مشابه
TRAP-TANDEM: data-driven extraction of temporal features from speech - Automatic Speech Recognition and Understanding, 2003. ASRU '03. 2003 IEEE Workshop on
Conventional features in automatic recognition of speech describe instantaneous shape of a short-term spectrum of speech. The TRAP-TANDEM features describe 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...
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تاریخ انتشار 2003