Extracting Forbidden Factors from Regular Stringsets

Abstract

The work presented here continues a program of completely characterizing the constraints on the distribution of stress in human languages that are documented in the StressTyp2 database with respect to the Local and Piecewise sub-regular hierarchies. We introduce algorithms that, given a Finite-State Automaton, compute a set of forbidden words, units, initial factors, free factors and final factors that define a Strictly Local (SL) approximation of the stringset recognized by the FSA, along with a minimal DFA that recognizes the residue set: the set of strings in the approximation that are not in the stringset recognized by the FSA. If the FSA recognizes an SL stringset, then the approximation is exact (otherwise it overgenerates). We have applied these tools to the 106 lects that have associated DFAs in the StressTyp2 database, a wide-coverage corpus of stress patterns that are attested in human languages. The results include a large number of strictly local constraints that have not been included in prior work categorizing these patterns with respect to the Local and Piecewise Sub-Regular hierarchies of Rogers et al. (2012), although, of course, they do not contradict the central result of that work, which establishes an upper bound on their complexity that includes strictly local constraints.