A Java Tool for Compiling Finite-State Transducers from Full-Form Lexicons
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HFST—A System for Creating NLP Tools
HFST—a System for Creating NLP Tools Krister Lindén, Erik Axelson, Senka Drobac, Sam Hardwick, Juha Kuokkala, Jyrki Niemi, Tommi A Pirinen, and Miikka Silfverberg University of Helsinki Department of Modern Languages Unioninkatu 40 A FI-00014 University of Helsinki, Finland {krister.linden, erik.axelson, senka.drobac, sam.hardwick, juha.kuokkala, jyrki.niemi, tommi.pirinen, miikka.silfverberg}@helsinki.fi Abstract. The paper presents and evaluates various NLP tools that have been created using the open source library HFST–Helsinki Finite- State Technology and outlines the minimal extensions that this has re- quired to a pure finite-state system. In particular, the paper describes an implementation and application of Pmatch presented by Karttunen at SFCM 2011. Keywords: finite-state technology, language identification, morpholog- ical guessers, spell-checking, named-entity recognition, language genera- tion, parsing, HFST, XFST, Pmatch Introduction In natural language processing, finite-state string transducer methods have been found useful for solving a number of practical problems ranging from language identification via morphological processing and generation to part-of-speech tag- ging and named-entity recognition, as long as the problems lend themselves to a formulation based on matching and transforming local context. In this paper, we present and evaluate various tools that have been created using HFST–Helsinki Finite-State Technology1 and outline the minimal exten- sions that this has required to a pure FST system. In particular, we describe an implementation of Pmatch presented by Karttunen at SFCM 2011 [7] and its application to a large-scale named-entity recognizer for Swedish. The paper is structured as follows: Section 1 is on applications and their evaluation. -
The Kleene Language for Weighted Finite-State Programming: User Documentation, Version 0.9.4.1
The Kleene Language for Weighted Finite-State Programming: User Documentation, Version 0.9.4.1 This Document is Work in Progress Corrections and Suggestions Are Welcome Kenneth R. Beesley SAP Labs, LLC P.O. Box 540475 North Salt Lake Utah 84054, USA [email protected] 7 July 2014 Copyright © 2014 SAP AG. Released under the Apache License, Version 2. http://www.apache.org/licenses/LICENSE-2.0.html Beesley i Preface What is Kleene? Kleene is a programming language that can be used to create many useful and efficient linguistic applications based on finite-state machines (FSMs). These applications include tokenizers, spelling checkers, spelling correc- tors, morphological analyzer/generators and shallow parsers. FSMs are also widely used in speech synthesis and speech recognition. Kleene allows programmers to define, build, manipulate and test finite- state machines using regular expressions and right-linear phrase-structure grammars; and Kleene supports variables, rule-like expressions, user-defined functions and familiar programming-language control syntax. The FSMs can include acceptors and two-projection transducers, either weighted un- der the Tropical Semiring or unweighted. If this makes no sense, the pur- pose of the book is to explain it. Pre-edited Kleene scripts can be run from the command line, and a graphical user interface is provided for interactive learning, programming and testing. Operating Systems Kleene runs on OS X and Linux, requiring Java version 1.6 or higher. Prerequisites This book assumes only superficial familiarity with regular languages, reg- ular relations and finite-state machines. While readers need not have any experience with finite-state program- ming, those who have no programming experience at all, e.g. -
Using Finite State Transducers for Multilingual Rule-Based Phonetic
Thesis submitted for the degree of Bachelor of Arts Using finite state transducers for multilingual rule-based phonetic transcription Author: Thora Daneyko Matrikelnr.: 3822667 Supervisor: Prof. Gerhard Jäger Eberhard Karls Universität Tübingen Philosphische Fakultät Seminar für Sprachwissenschaft Eidesstattliche Erklärung Hiermit versichere ich, dass ich die Arbeit selbständig verfasst, keine anderen als die angegebenen Hilfsmittel und Quellen benutzt, alle wörtlich oder sinngemäß aus anderen Werken übernommenen Aussagen als solche gekennzeichnet habe und dass die Arbeit weder vollständig noch in wesentlichen Teilen Gegenstand eines anderen Prüfungsverfahrens gewesen ist und dass die Arbeit weder voll- ständig noch in wesentlichen Teilen bereits veröffentlicht wurde sowie dass das in Dateiform eingereichte Exemplar mit den eingereichten gebundenen Exemplaren übereinstimmt. Tübingen, den Thora Daneyko Abstract EVOLAEMP is a current research project on comparative historical linguistics which is compiling a large lexical database called NorthEuraLex covering most languages of Northern Eurasia. To be able to compare the lexemes of these languages with their different writing systems and orthographies, NorthEuraLex aims to provide phonetic transcription in IPA for all entries. Because expert transcriptions are hard to obtain for smaller languages, automatic rule-based transcriptors have been developed. However, the current system is quite inefficient, resulting in bad performance especially on longer words. Thus, I develop and test a revision of this imple- mentation using finite state transducers (FST), which have previously proven to be very suitable for modeling phonological processes. The new implementation should perform faster and be able to operate on the system-independent rule sets already developed for 107 languages. The FST interface used in my system is the Helsinki Finite State Toolkit (HFST). -
This Document Is Sorted by Transfer Institution Name, Transfer Course
TRANSFER COURSE EQUIVALENCIES AS OF 5/2/2018 This document is sorted by Transfer Institution Name, Transfer Course Subject, and finally by JCU Equivaleny Course Subject Transfer Transfer Course JCU Equivalent JCU Equivalent JCU EquSCIalent Course Effective Institution Course Transfer Course Title JCU Equivalent Course Title Number Course Subject Course Number Attrutes (CORE) Term Subject Academy Of The Canyons FRNCH 101 ELEMENTARY FRENCH I FR 101 BEGINNING FRENCH 1 I 201610 Academy Of The Canyons HLHSCI 100 HEALTH EDUCATION EPA 2XX EXERCISE SCIENCE ELECTIVE 201610 Adrian College ACCT 203 PRIN OF ACCOUNTING I AC 201 ACCOUNTING PRINCIPLES 1 201610 Adrian College CHEM 105 GENERAL CHEMISTRY CH 141 GENERAL CHEMISTRY 1 SCI 201610 Adrian College CHEM 117 INTRO CHEMISTRY LAB I CH 143 GENERAL CHEMISTRY LAB 1 SCI 201610 Adrian College COMM 102 PRIN & PRAC OF PUBLIC SPEAKING CO 125 SPEECH COMMUNICATION 201610 Adrian College COMM 109 TELEVISION & RADIO ANNOUNCING CO 215 FUNDAMENTALS OF MEDIA PERFORM CA 201610 Adrian College MATH 115 PRE-CALCULUS GE 1XX GENERAL ELECTIVE 201610 Adrian College MLCS 102 SPANISH II SP 102 BEGINNING SPANISH 2 201610 Adrian College MUS 140 ADRIAN COLLEGE CHOIR FA 1XX FINE ARTS ELECTIVE CA 201610 Ajman Univ of Sci & Technology BASIC 102110 ISLAMIC CULTURE TRS 2XX THEOL & RELIGIOUS STUDIES ELEC 201625 Al Ma'arifaa International Sch CH 9CH01 AS LEVEL CHEMISTRY CH 142 GENERAL CHEMISTRY 2 SCI 201625 Al Ma'arifaa International Sch CH 9CH01 AS LEVEL CHEMISTRY CH 141 GENERAL CHEMISTRY 1 SCI 201625 Alabama State University CMS 205