Incremental Construction of Minimal Acyclic Sequential Transducers from Unsorted Data

TL;DR

This paper introduces an efficient, unsorted data-compatible algorithm for incrementally building minimal acyclic sequential transducers, improving upon previous methods that required sorted input data, with applications in pronunciation dictionaries.

Contribution

It generalizes existing automata construction methods to handle unsorted data for sequential transducers, eliminating the sorting requirement present in prior algorithms.

Findings

Algorithm efficiently constructs minimal acyclic sequential transducers from unsorted data.

The method is applicable to pronunciation dictionaries.

It outperforms previous algorithms that required sorted input.

Abstract

This paper presents an efficient algorithm for the incremental construction of a minimal acyclic sequential transducer (ST) for a dictionary consisting of a list of input and output strings. The algorithm generalises a known method of constructing minimal finite-state automata (Daciuk et al. 2000). Unlike the algorithm published by Mihov and Maurel (2001), it does not require the input strings to be sorted. The new method is illustrated by an application to pronunciation dictionaries.