1. A computer-implemented method performing, via a processor, operations of: determining a fuzzy rule to discriminate a speech segment from a non-speech segment, wherein an antecedent of the fuzzy rule includes an input variable indicating a characteristic of media data and an input variable membership, and wherein a consequent of the fuzzy rule includes an output variable indicating a likelihood of the media data being speech and an output variable membership; extracting an instance of the input variable from a segment; training an input variable membership function associated with the input variable membership and an output variable membership function associated with the output variable membership; operating the instance of the input variable, the input variable membership function, the output variable, and the output variable membership function, to determine whether the segment is the speech segment or the non-speech segment; fuzzifying the input variable based upon the instance of the input variable and the input variable membership function, to provide a fuzzified input indicating a first degree that the input variable belongs to the input variable membership; reshaping the output variable membership function based upon the fuzzified input, to provide an output set indicating a group of a second degree that the output variable belongs to the output variable membership; defuzzifying the output set to provide a defuzzified output; labeling whether the segment is the speech segment or the non-speech segment based upon the defuzzied output; finding a centroid of the output set to provide the defuzzified output, if the fuzzy rule comprises one rule; multiplying each of a plurality of weights with the output set obtained through each of the plurality of rules, to provide each of a plurality of weighted output sets, if the fuzzy rule comprises a plurality of rules; aggregating the plurality of weighted output sets to provide an output union; and finding a centroid of the output union to provide the defuzzied output.
1. A computer-implemented method performing, via a processor, operations of: determining a fuzzy rule to discriminate a speech segment from a non-speech segment, wherein an antecedent of the fuzzy rule includes an input variable indicating a characteristic of media data and an input variable membership, and wherein a consequent of the fuzzy rule includes an output variable indicating a likelihood of the media data being speech and an output variable membership; extracting an instance of the input variable from a segment; training an input variable membership function associated with the input variable membership and an output variable membership function associated with the output variable membership; operating the instance of the input variable, the input variable membership function, the output variable, and the output variable membership function, to determine whether the segment is the speech segment or the non-speech segment; fuzzifying the input variable based upon the instance of the input variable and the input variable membership function, to provide a fuzzified input indicating a first degree that the input variable belongs to the input variable membership; reshaping the output variable membership function based upon the fuzzified input, to provide an output set indicating a group of a second degree that the output variable belongs to the output variable membership; defuzzifying the output set to provide a defuzzified output; labeling whether the segment is the speech segment or the non-speech segment based upon the defuzzied output; finding a centroid of the output set to provide the defuzzified output, if the fuzzy rule comprises one rule; multiplying each of a plurality of weights with the output set obtained through each of the plurality of rules, to provide each of a plurality of weighted output sets, if the fuzzy rule comprises a plurality of rules; aggregating the plurality of weighted output sets to provide an output union; and finding a centroid of the output union to provide the defuzzied output. 4. The method of claim 1 , wherein the input variable comprises at least one variable selected from a group of percentage of low-energy frames (LEFP), high zero-crossing rate ratio (HZCRR), variance of spectral centroid (SCV), variance of spectral flux (SFV), variance of spectral roll-off point (SRPV) and 4 Hz modulation energy (4 Hz).