Disambiguation of finite-state transducers (original) (raw)
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Finite-State Transducers in Language and Speech Processing
Finite-state machines have been used in various domains of natural language processing. We consider here the use of a type of transducer that supports very efficient programs: sequential transducers. We recall classical theorems and give new ones characterizing sequential string-tostring transducers. Transducers that output weights also play an important role in language and speech processing. We give a specific study of string-to-weight transducers, including algorithms for determinizing and minimizing these transducers very efficiently, and characterizations of the transducers admitting determinization and the corresponding algorithms. Some applications of these algorithms in speech recognition are described and illustrated.
Factorization of Finite-State Transducers
Finite-state transducers and finite-state automata are efficient and natural representations for a large variety of problems. We describe a new algorithm for turning a finite-state transducer into the composition of two deterministic finite-state transducers such that the combined size of the derived transducers can be exponentially smaller than other known deterministic constructions. As a consequence, this can also be used to build deterministic representations of finite-state automata smaller than the minimal finite-state automata computed by the classic determinization and minimization algorithms. We also report experimental results on large scale dictionaries and rule-based systems. This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such ...
Parallel intersection and serial composition of finite state transducers
1988
We describe a linguistically expressive and easy to implement parallel semantics for quasi-deterministic finite state transducers (FSTS) used as acceptors. Algorithms are given for detemaining acceptance of pairs of phoneme strings given a parallel suite of such transducers and for constructing the equivalent single transducer by parallel intersection. An algorithm for constructing the serial composition of a sequence of such transducers is also given. This algorithm can produce generally nondetemlinislic FSTS and an algorithm is presented for eliminating the unacceptable nondeterminism. Finally, the work is discussed in the context of other work on finite state transducers.
Inference of finite-state transducers from regular languages
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Finite-state transducers are models that are being used in different areas of pattern recognition and computational linguistics. One of these areas is machine translation, where the approaches that are based on building models automatically from training examples are becoming more and more attractive. Finite-state transducers are very adequate to be used in constrained tasks where training samples of pairs of sentences are available. A technique to infer finite-state transducers is proposed in this work. This technique is based on formal relations between finite-state transducers and finite-state grammars. Given a training corpus of input-output pairs of sentences, the proposed approach uses statistical alignment methods to produce a set of conventional strings from which a stochastic finite-state grammar is inferred. This grammar is finally transformed into a resulting finitestate transducer. The proposed methods are assessed through series of machine translation experiments within the framework of the EUTRANS project.
Beyond the Horizon of Computability, 2020
An iterated uniform finite-state transducer (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\textsc {iufst}$$\end{document}) operates the same length-preserving transduction, starting with a sweep on the input string and then iteratively sweeping on the output of the previous sweep. The \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\textsc {iufst}$$\end{document} accepts or rejects the input string by halting in an accepting or rejecting state along its sweeps. We consider both the deterministic (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{a...
Translation with cascaded finite state transducers
2000
Abstract In this paper we discuss the use of cascaded finite state transducers for machine translation. A number of small, dedicated transducers is applied to convert sentence pairs from a bilingual corpus into generalized translation patterns. These patterns, together with the transducers are then used as a hierarchical translation memory for fully automatic translation. Results on the German--English VERBMOBIL corpus are given.
A Programming Language for Finite State Transducers
Lecture Notes in Computer Science, 2006
This paper presents SFST-PL, a programming language for finite state transducers which is based on extended regular expressions with variables. The programming language is both simple and general and suitable for a wide range of possible applications. A compiler for the programming language is provided by the SFST tools which have successfully been used to implement a large-scale German morphology.
Probabilistic and Frequency Finite-State Transducers
A transducer is a finite-state automaton with an input and an output. We compare possibilities of nondeterministic and probabilistic transducers, and prove several theorems which establish an infinite hierarchy of relations computed by these transducers. We consider only left-total relations (where for each input value there is exactly one allowed output value) and Las Vegas probabilistic transducers (for which the probability of any false answer is 0). It may seem that such limitations allow determinization of these transducers. Nonetheless, quite the opposite is proved; we show a relation which can only be computed by probabilistic (but not deterministic) transducers, and one that can only be computed by nondeterministic (but not probabilistic) transducers. Frequency computation was introduced by Rose and McNaughton in early sixties and developed by Trakhtenbrot, Kinber, Degtev, Wechsung, Hinrichs and others. It turns out that for transducers there is an infinite hierarchy of relations computable by frequency transducers and this hierarchy differs very much from similar hierarchies for frequency computation by a) Turing machines, b) polynomial time Turing machines, c) finite state acceptors.