Revision as of 21:01, 10 May 2017

Transducer for Hiaki

For my final project, I created a prototype transducer for the Hiaki language, a language extremely lacking in computational resources. It is available at Swarthmore's github.

Implementation

The implementation includes the following notable or unusual functonality, in addition to standard treatment of nouns, verbs, pronouns, postpositions, adjectives, adverbs, and other common Hiaki word types:

Variation in Verb Forms

Hiaki verb forms exhibit somewhat idiosyncratic variation in their roots depending on whether derivational suffixation appears. This process could not be automated because of the idiosyncracy, but the lexicon is built so both forms of a root verb can be placed and the transducer will be sure only to generate the right one.

Examples:

• poona (without morphology) to pon (with morphology)
• kiima (without morphology) to kima'a (with morphology)
• ne'e (without morphology) to ni'i (with morphology)

As the above examples illustrate, this change is unpredictable; it can involve addition of letters, change of letters, or deletion of letters. For this reason it must be hard-coded into the transducer.

An important next step to the transducer would be to make sure both forms of all verbs are included; this would require consultation with a speaker, as no dictionaries I have found consistently include both forms.

Noun Incorporation

Hiaki nouns and pronouns can be incorporated into verbs, losing their case morphology and becoming part of the single word. The transducer is structured to handle incorporation of arbitrary nouns into arbitrary verbs.

Due to the computational complexity of noun incorporaiton, it is currently disabled. However, pronoun incorporation, which occurs vastly more frequently in the corpus, remains enabled.

Reduplication

Many Hiaki verbs reduplicate productively to indicate, for instance, the habitual aspect on verbs, or plurality on adjectives. Functionality for reduplication is partially implemented using .twol rules. However, due to the complexity of Hiaki reduplication and the idiosyncracies across verbs regarding what part of the verb reduplicates, the implementation should not yet be considered complete.

Some "reduplications" are not actually reduplications; these appear on verbs which have a different morphological change in place of reduplication for the same semantic effect. Such "reduplications", which can be, for example, gemination of a consonant in the middle of the word, are hard-coded.

Examples of Reduplication Types:

• wiuta to wiwiuta (open syllable reduplication)
• kupikte to kupikupikte (two open syllable reduplication)
• hakta to hakhakta (closed syllable reduplication)
• maveta to mavveta (gemination -- not actually reduplication)

Next Steps

Several major grammatical aspects of the Hiaki language remain unimplemented, for example:

Number Suppletion

Many Hiaki verbs completely change root form depending on the number of one of their arguments, usually the object if the verb is transitive and the subject otherwise. This is implemented in the transducer with <sg> and <pl> tags on verbs for those verbs known to exhibit number agreement; however, it is often the case in dictionaries and word databases that it is not made clear if a verb root is singular, plural, or both. More work needs to be done with the transducer to implement this properly.

Vowel Change Rules

The vowel change rules in Hiaki are fairly complex, and the forms of affixes often vary in slight ways depending on the root. The transducer needs to be improved by first identifying the regularities and patterns in the alternation of affixes, then implementing them, probably through .twol. Currently some such patterns are implemented, but normally the transducer overgenerates, placing every form of a given affix on any root. There are also likely forms we have not encountered to put in the transducer.

Evaluation

Coverage was tested over a corpus. Little text is readily available in Hiaki, so the corpus used only has 3254 words. To continue work on the transducer, it is likely a larger corpus would need to be compiled.