Editing Dynamic time warping (section)

===Spoken-word recognition===
Due to different speaking rates, a non-linear fluctuation occurs in speech pattern versus time axis, which needs to be eliminated.<ref  name="Sakoe78">{{cite journal|last1=Sakoe|first1=Hiroaki|last2=Chiba|first2=Seibi|title=Dynamic programming algorithm optimization for spoken word recognition|journal=IEEE Transactions on Acoustics, Speech, and Signal Processing|volume=26|issue=1|pages=43–49|doi=10.1109/tassp.1978.1163055|year=1978|s2cid=17900407 }}</ref> DP matching is a pattern-matching algorithm based on [[Dynamic programming|dynamic programming (DP)]], which uses a time-normalization effect, where the fluctuations in the time axis are modeled using a non-linear time-warping function. Considering any two speech patterns, we can get rid of their timing differences by warping the time axis of one so that the maximal coincidence is attained with the other. Moreover, if the warping function is allowed to take any possible value, {{clarify span|very less|date=October 2017}} distinction can be made between words belonging to different categories. So, to enhance the distinction between words belonging to different categories, restrictions were imposed on the warping function slope.