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Eight HFUs were recognized using porosity-permeability core data and FZI* (Flow Zone Indicator-Star) method.
So, a clean version of the speech is recognized using the clean models.
These corner frequencies are easily recognized using the published data in the Fourier domain.
Piano and Clarinet tones were better recognized using Smt-MF mapping.
So far, the IMOP families are recognized using the MCA method.
So the noisy speech is recognized using noisy models [19, 20].
Highly Influenceable parameters of Signal to Noise Ratio are recognized using Analysis of Variance (ANOVA).
The needs of the system are recognized using the term Total Dynamic Head (TDH).
However, in everyday life, human motion can also be recognized using acoustic cues.
Therefore, input speech signals with estimated C 50 higher than 23 dB are recognized using clean-condition HMMs, whereas signals with C 50 lower than this threshold are recognized using multi-condition HMMs.
This point could be recognized using microscope and camera at the production port and throughout the micro-model.
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