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The sampling frequency of the speech is 8 kHz.
The fundamental frequency of the speech signal can be estimated by finding maxima of an autocorrelation function of the sampled signal ( {x}_m ) and the segment ( {s}_m ), given by {z}_k={varSigma}_{m=1}^{M_s}{s}_m{x}_{m+k}.
Similar(58)
The recorded emotional speech is emphasized by passing through a filter to increase the magnitude of the higher frequencies of the speech signal.
This is generally justified because experimental results have shown that lower frequencies of the speech spectrum carry more crucial information for ASR than higher frequencies; therefore, these frequencies are generally emphasized by a nonlinear warping function.
is given by the characteristic frequency of the place where the cross-section is taken, while is determined by the fundamental frequency of this speech segment.
It reduces the effect of leakage for the better representation of the frequency spectrum of the speech signals.
The speech signal first undergoes pre-emphasis (with a coefficient of 0.97), which flattens the frequency characteristics of the speech signal.
It diminishes the effect of varying vocal tract length among different speakers by warping the frequency axis of the speech power spectrum during signal analysis [19].
The central frequencies of the GT filter banks are distributed in a quasi-logarithmic form and are evenly distributed in the frequency range of the speech signal based on the equivalent rectangular bandwidth (ERB).
In this case, the cost functions for the vocal tract are used, and formants are also considered, which results in more information about the frequency domain of the speech being available, making the estimated results more reliable.
In the third stage, the fundamental frequency of the target speech is extracted from the initial foreground stream and it is used to mark units as speech dominant or interference dominant.
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