@classmethod
    def adjustUNKLMScore(cls, cand_hyp, featVec):
        lm_indx = 0
        lmFeats = []
        for lm_obj in cls.lmLst:
            if cls.no_dscnt_UNKlm: lmFeats.append( str("%g" % featVec[lm_indx]) )
            else: lmFeats.append( str("%g" % (featVec[lm_indx] - lm_obj.calcUNKLMScore(cand_hyp))) )
            lm_indx += 1

        return ' '.join(lmFeats)
dataset/ETHPy150Open sfu-natlang/Kriya/src/Kriya-Decoder/languageModelManager.py/LanguageModelManager.adjustUNKLMScore/original