Segmental Environments of Spanish Diphthongization

by Adam Albright, Argelia Andrade, and Bruce Hayes

Department of Linguistics, UCLA

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Abstract

Spanish diphthongization is a well-known example of an exceptionful phonological alternation. Although many forms do exhibit an alternation (e.g. [sentámos] ~ [sjénto] ‘we/I sit’, [kontámos] ~ [kwénto] ‘we/I count’), many others do not (e.g. [rentámos] ~ [rénto] ‘we/I rent’, [montámos] ~ [mónto] ‘we/I mount’). Previous accounts of the alternation have largely accepted this unpredictability at face value, focusing on setting up appropriate lexical representations to distinguish alternating from non-alternating roots. Our interest here is in whether Spanish speakers go beyond this, internalizing rich and detailed knowledge of the ways in which diphthongization is conditioned by the segmental environments.

We employed a machine-implemented algorithm to search a database of 1698 mid-vowel verbs. The algorithm yielded a large stochastic grammar, specifying the degree to which diphthongization is favored or disfavored in particular segmental contexts. We used this grammar to make predictions about the well-formedness of novel roots. The predictions were then checked in a "wug"-testing experiment with 96 native speaker consultants. We found that the consultants’ intuitions (both in volunteered forms and in acceptability ratings) were significantly correlated with the predictions of the algorithmically-learned grammar. Our conclusion is that Spanish speakers can indeed use detailed segmental environments to predict diphthongization. We discuss this conclusion in light of various models of linguistic irregularity.

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Related files:

• A complete break-down of all of the data, along with all of the predictions from various modeling attempts, can be found in the two Excel files contained in SpanDiphAllData.zip
• The input and output files for all of the simulations using the minimal generalization learner can be found in SpanDiphSimulations.zip
• The results of the GLA simulation can be found in GLASimulation.zip.
• The database of verbs from LexEsp used in this study is contained in SpanVerbs.zip
• More information about the minimal generalization computational learning model can be found here

Last updated: 7/18/00