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It is one of the most highly debated issues in loanword phonology whether loanword adaptations are phonologically or phonetically driven. This paper addresses this issue and aims at demonstrating that only the acceptance of both a phonological as well as a phonetic approximation stance can adequately account for the data found in Japanese. This point will be exemplified with the adaptation of German and French mid front rounded vowels in Japanese. It will be argued that the adaptation of German /oe/ and /ø/ as Japanese /e/ is phonologically grounded, whereas the adaptation of French /oe/ and /ø/ as Japanese /u/ is phonetically grounded. This asymmetry in the adaptation process of German and French mid front rounded vowels and further examples of loans in Japanese lead to the only conclusion that both strategies of loanword adaptation occur in languages. It will be shown that not only perception, but also the influence of orthography, of conventions and the knowledge of the source language play a role in the adaptation process.
This paper proposes an annotating scheme that encodes honorifics (respectful words). Honorifics are used extensively in Japanese, reflecting the social relationship (e.g. social ranks and age) of the referents. This referential information is vital for resolving zero
pronouns and improving machine translation outputs. Annotating honorifics is a complex task that involves identifying a predicate with honorifics, assigning ranks to referents of the
predicate, calibrating the ranks, and connecting referents with their predicates.
While the sortal constraints associated with Japanese numeral classifiers are well-studied, less attention has been paid to the details of their syntax. We describe an analysis implemented within a broad-coverage HPSG that handles an intricate set of numeral classifier construction types and compositionally relates each to an appropriate semantic representation, using Minimal Recursion Semantics.
The Deep Linguistic Processing with HPSG Initiative (DELH-IN) provides the infrastructure needed to produce open-source semantic transfer-based machine translation systems. We have made available a prototype Japanese-English machine translation system built from existing resources include parsers, generators, bidirectional grammars and a transfer engine.