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NTIS 바로가기IEEE transactions on speech and audio processing : a publication of the IEEE Signal Processing Society, v.9 no.3, 2001년, pp.196 - 200
Potamianos, A. (Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA) , Maragos, P.
The use of general time-frequency distributions as features for automatic speech recognition (ASR) is discussed in the context of hidden Markov classifiers. Short-time averages of quadratic operators, e.g., energy spectrum, generalized first spectral moments, and short-time averages of the instantaneous frequency, are compared to the standard front end features, and applied to ASR. Theoretical and experimental results indicate a close relationship among these feature sets.
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