Analysis of Speech Using Different Methods
Abstract
In speech analysis, the voiced-unvoiced decision is usually performed in extracting the information from the speech signals. In this paper, two methods are performed to separate the voiced and unvoiced parts of the speech signals. 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 whereas the energy is high for voiced part and low for unvoiced part. Therefore, these methods are proved effective in separation of voiced and unvoiced speech.
Keywords: Implementation, low-energy, root mean square (RMS) power, speech, variance, voiced, unvoiced, ZCR: zero-crossing rate
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