In this paper, we present a new algorithm that can identify in polynomial time and data using positive examples any class of subsequential functions that share a particular finite-state structure. While this structure is given to the learner a priori, it allows for the exact learning of partial functions, and both the time and data complexity of the… (More)
The Tier-based Strictly 2-Local (TSL 2) languages are a class of formal languages which have been shown to model long-distance phonotactic generalizations in natural language (Heinz et al., 2011). This paper introduces the Tier-based Strictly 2-Local Inference Algorithm (2TSLIA), the first non-enumerative learner for the TSL 2 languages. We prove the 2TSLIA… (More)
Autosegmental phonology represents words with graph structures. This paper introduces a way of reasoning about autosegmental graphs as strings of concatenated graph primitives. The main result shows that the sets of au-tosegmental graphs so generated obey two important, putatively universal, constraints in phonological theory provided that the graph… (More)
We present a theory of phonology based on the computational properties of input-output mappings. These properties define restrictive classes of mappings which are learnable by a provably correct, efficient algorithm. The algorithm learns both the active surface constraints and the repairs, including opaque mappings.
We compared the stress pattern data found in Jeffrey Heinz's Stress Pattern Database (SPD) and Harry van der Hulst and Rob Goedemans' StressTyp (ST1) database, in order to convert both to one format so that they could be merged into a singular database (StressTyp 2, ST2). A primary issue was the differing descriptive shorthands to represent the source text… (More)