However, as features of articulatory phonetics are manually assigned, these algorithms fall short in capturing the perceptual essence of phonetic similarity through empirical data (Kessler, 2005).
dIMSIM achieves high accuracy by learning the encodings both from high quality training data sets and linguistic Pinyin features.