1. An audio signal segmentation algorithm comprising: providing an audio signal; applying an audio activity detection (AAD) step to divide the audio signal into at least one first audio segment and at least one second audio segment, wherein the audio activity detection step further comprises: dividing the audio signal into a plurality of frames; applying a frequency transformation step to signals in each of the frames to obtain a plurality of bands in each frame; performing a likelihood computation step to the bands and a noise parameter to obtain a likelihood ratio therebetween; performing a comparison step to the likelihood ratio and a noise threshold, if the noise threshold is greater than the likelihood ratio, the bands belonging to a first frame, and if the likelihood ratio is greater than the noise threshold, the bands belonging to a second frame wherein the first frame belongs to the first audio segment and the second frame belongs to the second audio segment; and when a distance between two adjacent second frames is smaller than a predetermined value, combining the two adjacent second frames to compose the second audio segment, performing an audio feature extraction step on the second audio segment to obtain a plurality of audio features of the second audio segment; applying a smoothing step to the second audio segment after the audio feature extraction step; and discriminating a plurality of speech frames and a plurality of music frames from the second audio segment wherein the speech frames and the music frames compose at least one speech segment and at least one music segment, respectively.
10. The audio signal segmentation algorithm according to claim 1 , wherein the smoothing step further comprises performing a convolution process to the second audio segment after the audio feature extraction step and a window.