*3.1.1 The ZCR algorithm*

The ZCR algorithm can be defined as the number of crossing the signal the zero axis within a specific window. It is widely used because its simplicity and robustness [34]. We may define the ZCR as in the following equation.

$$Z\_n = \frac{1}{2N} \sum\_{m=n-N+1}^{N} |\text{sgn}\left[\mathbf{x}(m)\right] - \text{sgn}\left[\mathbf{x}(m-1)\right]|\tag{1}$$

where *Zn* is the ZCR, *N* is the number of samples in one window, and *sgn* is the sign of the signal such that *sgn* [*x*(*n*)] = 1 when *x*(*n*) > 0, *sgn* [*x*(*n*)] = �1, when *x*(*n*) < 0. An essential not is that the sampling rate must be high enough to catch any crossing through zero. Another important note before evaluating the ZCR is to normalize the signal by subtracting its average value. It is clear from Eq. (1) that the value of the ZCR is proportional to the sign change in the signal, i.e., the dominant frequency of *x*(*n*). Therefore, we may find that the ZCR of music is, in general, higher than that of audio, but not sure at the unvoiced audio.
