The morphological systems of natural languages are replete with examples of
the same devices used for multiple purposes: (1) the same type of morphological
process (for example, suffixation for both noun case and verb tense) and (2)
identical morphemes (for example, the same suffix for English noun plural and
possessive). These sorts of similarity would be expected to convey advantages
on language learners in the form of transfer from one morphological category to
another. Connectionist models of morphology acquisition have been faulted for
their supposed inability to represent phonological similarity across
morphological categories and hence to facilitate transfer. This paper describes
a connectionist model of the acquisition of morphology which is shown to
exhibit transfer of this type. The model treats the morphology acquisition
problem as one of learning to map forms onto meanings and vice versa. As the
network learns these mappings, it makes phonological generalizations which are
embedded in connection weights. Since these weights are shared by different
morphological categories, transfer is enabled. In a set of experiments with
artificial stimuli, networks were trained first on one morphological task
(e.g., tense) and then on a second (e.g., number). It is shown that in the
context of suffixation, prefixation, and template rules, the second task is
facilitated when the second category either makes use of the same forms or the
same general process type (e.g., prefixation) as the first.Comment: 21 pages, uuencoded compressed Postscrip