This product presentation describes the integration of the three MT technologies currently used – rule-based (RBMT), Statistical (SMT) and Neural (NMT) – into one scalable single platform, OctaveMT. MT clients can access all three types of MT engines, whether on a user specified basis or depending on several translation parameters (language-direction, domain, etc.)

The morphology of inflectional languages poses specific problems in the processing of morphological alternations. Regular alternations at morpheme boundaries can be elegantly captured by the use of rule formalisms based on the two-level morphology model. Stem alternations and completely irregular alternations at morpheme boundaries, however, need to be captured in some way in the lexicon. This paper presents four possible solutions to the problem and makes a claim in favor of one of them. The proposed approach makes use of feature bundles that contain the necessary linguistic information to uniquely identify allomorphic variations of stems in the lexicon. The proposal is an improvement in that it simplifies the representation of allomorphic variations in the lexicon by avoiding duplication of stem allomorphs to capture cross-combination of several morphosyntactic features in stem+flex sequences.