In this paper, we perform spatio-spectral analysis of the human cortex with implanted electrocorticographic (ECoG) electrodes during the voice production process. For this study, the ECoG signals were recorded while the subject performed two-syllable tasks. Additionally, assuming that the speech activity of a subject is expressed as ECoG signal activity disparately distributed over the space of the electrodes, we examined the spectral information in response to the electrode locations. The study was based on spectral features (power spectral density) estimated for each electrode. Quantitative analysis based on the Relief algorithm was followed to estimate the degree of importance of each electrode for describing the voice activity. The experimental results showed that the spectral analysis with resolution of 8 Hz offers the highest voice discrimination performance (94.2%) using support vector machines as classifier. Finally, our analysis showed that during voice activity the frequency bands [168, 208] Hz are mostly affected.