Morphological inflection is the task of generating previously unseen words from morphological features. A common approach, the morpheme-based approach, decomposes words into smaller units, such as morphemes or affixes, learned in advance. This paper proposes a different approach. It shows that breaking words into pieces is not necessarily the best option. The proposed approach is holistic and treats whole word forms as basic units in its description of morphological variations among word forms. The approach generates inflected forms by solving analogical equations between whole word forms; morphological features can be used as constraints. Experiment results on the 52 languages of SIGMORPHON 2017 Shared Task show that the proposed approach performs as good as the morpheme-based approach, even slightly better on average. This demonstrates the absence of necessity of explicitly learning how to decompose words.
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