Understanding GCC-PHAT as a Feature
Let there be two microphones, $x_1(t), x_2(t)$ capturing a source, $s(t)$, with some additive noise $n_{1,2}(t)$ that is uncorrelated with the source and with each other (i.e., its effect can be ignored while calculating the cross-correlation). Let $\tau_0$ (in seconds) be the time difference of arrival between the two microphones. The time domain equations of the microphones are
$$x_1(t) = s(t) + n_1(t) \\
        x_2(t) = \alpha_0 s(t - \tau_0) + n_2(t) $$
Now, taking the FFT and converting these to the frequency domain would give us,
$$
        X_1(\omega) = S(\omega) + N_1(\omega) \\
        X_2(\omega) = \alpha_0 S(\omega) \exp{(-j\omega \tau_0)} + N_2(t) 
$$
The cross correlation function of the two microphone signals (or the cross-power spectrum in the frequency domain), can be written as
$$      \begin{aligned} R_{x_1,x_2}(l) &amp;= \mathbb{E}[x_1(t) x_2(t-l)] \\
        R_{x_1, x_2}(\omega) &amp;= X_1(\omega)X_2^*(\omega) \\
                             &amp;= |S(\omega)|^2 \alpha_0 \exp{(j\omega \tau_0)}
        \end{aligned} 
$$
The Generalized Cross-Correlation function with Phase Transform (GCC-PHAT) at lag $l$ is defined as
$$ \begin{aligned}
\tilde{R}_{x_1,x_2}(l) =&amp; \frac{1}{2\pi} \int_{-\pi}^{\pi} \frac{R_{x_1,x_2}(\omega)}{|R_{x_1,x_2}(\omega)|}e^{j\omega l}d\omega \\
=&amp;  \frac{1}{2\pi} \int_{-\pi}^{\pi} e^{j\omega(l + \tau_0)} d\omega \\
&amp;= \delta(l - \tau_0)
\end{aligned} $$
where $\delta$ is the Dirac-delta function which is non-zero at $l = \tau_0$, which is the time-difference of arrival (TDOA). Typically, the lag is calculated in samples, so to convert that to seconds, you have to divide it by the sampling rate.
I hope this helps in understanding GCC-PHAT, which is useful tool for TDOA estimation, and hence, source localization.