1 Separation of Voiced and Unvoiced using Zero crossing rate and Energy of the Speech Signal

In speech analysis, the voiced-unvoiced decision is usually performed in extracting the information from the speech signals. In this paper, we performed two methods to separate the voicedunvoiced parts of speech from a speech signal. These are zero crossing rate (ZCR) and energy. In here, we evaluated the results by dividing the speech sample into some segments and used the zero crossing rate and energy calculations to separate the voiced and unvoiced parts of speech. The results suggest that zero crossing rates are low for voiced part and high for unvoiced part where as the energy is high for voiced part and low for unvoiced part. Therefore, these methods are proved more effective in separation of voiced and unvoiced speech.