Open Source Java Linguistics Software
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Java Linguistics Software
View 2715 business solutionsBrowse free open source Java Linguistics Software and projects below. Use the toggles on the left to filter open source Java Linguistics Software by OS, license, language, programming language, and project status.
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Wordcorr
Data management for comparative linguistics
Wordcorr automates the tedious and risky process of tabulating and managing the sound correspondences used in working out the historical development of natural languages. Initial support was from NSF. -
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Korean Analyzer Rhino
Parsing Korean words by morpheme and part-of-speech
RHINO parses Korean words by morpheme and part-of-speech. Its dictionaries are based on Korean Modern Tagged Corpus(12 million phrases scale) which was made by Korean government. So it analyses many cases of stems and endings. And the newly developed Dynamic Dictionary Technology can make words to react with their context. That is, a programmed database. For more information see the files in the help folder. -
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sgmweka
Weka wrapper for the SGM toolkit for text classification and modeling.
Weka wrapper for the SGM toolkit for text classification and modeling. Provides Sparse Generative Models for scalable and accurate text classification and modeling for use in high-speed and large-scale text mining. Has lower time complexity of classification than comparable software due to inference based on sparse model representation and use of an inverted index. The provided .zip file is in the Weka package format, giving access to text classification. Other functions are usable through either Java command-line commands or class inclusion into Java projects. -
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OO Pinyin Guide is a Java extension for OpenOffice 3 or higher. It enables the user to add pinyin transliteration over Chinese characters inside a text document. This tool can be useful for people learning or teaching Chinese.
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LaBB-CAT
A linguistic annotation store
LABB-CAT is a browser-based linguistics research tool that stores recordings and regular-expression searchable text transcripts of interviews. The search results, entire transcripts, and media, can be viewed or exported in a variety of format -
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Ghawwas_V4
An open source system for Arabic corpora processing
Ghawwas (previously known as Khawas) is an open source system for Arabic corpora processing. Ghawwas V4.0 provides the following main functions: a. Frequency list for single word and N-Grams b. Concordance c. Collocation (MI, CHI Squared, LL, T-Score, Z Score, Dice, Log Dice, Weirdness Coefficient) d. Lexical patterns search e. Two corpora frequency profile comparison based on MI, CHI, LL, T-Score, Z Score, Dice, Log Dice, Weirdness Coefficient f. Accept Windows and UTF-8 character encoding g. Accept TXT, DOC, DOCX, RTF and HTML formats h. Export the processing results in CSV file format -
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The Helsinki Finite-State Transducer toolkit is intended for processing natural language morphologies. The toolkit is demonstrated by wide-coverage implementations of a number of languages of varying morphological complexity.
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TXM
Unicode XML TEI text analysis platform
TXM is a free and open-source cross-platform Unicode & XML based text analysis environment and graphical client, supporting Windows, Linux and Mac OS X. It can also be used online as a J2EE standard compliant web portal (GWT based) with access control built in. DOWNLOAD LATEST VERSION OF TXM : http://textometrie.ens-lyon.fr/spip.php?rubrique61&lang=en TXM offers a comprehensive range of analysis tools (concordances, collocate search, frequency lists, etc.) based on the powerfull CQP full text search engine (http://cwb.sourceforge.net) and a range of statistical functions (factorial analysis, classification, cooccurrency analysis, etc.) based on R packages (http://www.r-project.org). Read the scientific background at the Textométrie project web site http://textometrie.ens-lyon.fr/?lang=en. Read a full description at the TEI Tools wiki http://wiki.tei-c.org/index.php/TXM. -
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Musaheb
An Arabic collocation extraction tool
“Musaheb”, an Arabic collocation extraction tool that has been designed and implemented to overcome the limitations of existing collocation extraction tools. “Musaheb” is able to extract n-gram collocations up to 5-gram, in addition to extracting the collocates of the nodes (the word-types we are looking for its collocates) within a window size of zero to 15 words. Moreover, it provides eight collocation statistics to calculate the strength of the collocation, and permits the input of various constraints during node selection and collocate extraction. Based on the user preferences for the node, concordance and collocates selection, the tool saves all nodes and their associated collocates in an XML file; allowing easy conversion to different formats. -
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BioC
We describe a simple XML format to share text documents and annotation
A minimalist approach to share text documents and data annotations. Allows a large number of different annotations to be represented. Project files contain: - simple code to hold/read/write data and perform sample processing. - BioC-formatted corpora - BioC tools that work with BioC corpora BioC goals - simplicity - interoperability - broad use - reuse There should be little investment required to learn to use a format or a software module to process that format. We are interested in reuse, and we focus on common NLP tasks that are broadly useful for textmining. -
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Thinknowlogy
The world's only naturally intelligent knowledge technology
Natural intelligence is the utilization of naturally occurring logic. This naturally occurring logic provides concrete clues for organizing natural objects, like: - Grouping objects that belong together, - Separating objects that don't belong together, - Archiving objects that have become less important. Natural language and spatial information are sources of natural intelligence: - Natural language is providing concrete logic for organizing knowledge objects, - Spatial information provides concrete logic for organizing spatial objects (utilized in, e.g., self-driving cars). In this way, our brains know how to organize their knowledge and spatial information. I focus on natural language because this source of natural intelligence is hardly understood by scientists. Hence, the inability of Large Language Models to organize changes in their knowledge independently. -
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srt-translator
Subtitle translator from one natural language to other.
Translating subtitles in format SubRip from one natural language to other. It is based on Google Translate without API and therefore without payment. Translator have automatic and manual spell checkers. -
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RDRPOSTagger
A Rule-based Part-of-Speech and Morphological Tagging Toolkit
RDRPOSTagger is a robust, easy-to-use and language-independent rule-based toolkit for Part-of-Speech (POS) and morphological tagging. RDRPOSTagger obtains fast performance in both learning and tagging process. RDRPOSTagger also achieves a very competitive accuracy in comparison to the state-of-the-art results. RDRPOSTagger now supports pre-trained POS and morphological tagging models for Bulgarian, Czech, Dutch, English, French, German, Hindi, Italian, Portuguese, Spanish, Swedish, Thai and Vietnamese. Additionally, RDRPOSTagger supports the pre-trained Universal POS tagging models for 40 languages. See the full usage of RDRPOSTagger at: http://rdrpostagger.sourceforge.net/ -
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Corpus Toolkit
A text management tool for linguistic purposes...
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FREJ stands for "Fuzzy Regular Expressions for Java" - it is a command-line tool and library which allow you easily compare strings with patterns disregarding nasty typos and considering several variants (like "Barack Obama", "B.H.Obama" etc.) Project sources are moved to github: https://github.com/RodionGork/FREJ
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NetBeans Dictionaries
Additional dictionary files for the NetBeans spellchecker.
Additional dictionary files for the NetBeans spellchecker. -
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OPTIMA cidoc-crm Semantic Annotation
Semantic annotation of archaeology reports with respect to CIDOC-CRM
The semantic annotation system OPTIMA is the result of Andreas Vlachidis PhD work, (supervised by Prof. Douglas Tudhope, University of Glamorgan, UK). OPTIMA performs the NLP tasks of Named Entity Recognition, Relation Extraction, Negation Detection and Word Sense Disambiguation using hand-crafted rules and SKOS terminological resources (English Heritage Thesauri and Glossaries). The resulted semantic annotations are associated with classes of the (ISO 21127:2006) CIDOC Conceptual Reference Model (CRM) and its archaeological extension, CRM-EH. OPTIMA is also targeted at the detection and recognition of contextual relations between CRM entities. Such relations are modeled with respect to the CRM-EH archaeology extension. The pipeline targets the CIDOC-CRM entities; E19.Physical_Object, E53.Place, E49.Time_Appellation and E57.Material and the CRM-EH entities; EHE1001.Context_Event, EHE1002.Production_Event, EHE1004.Deposition_Event and P45.consists_of material property -
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Stemmer Gujarati
Offline stemmer for Gujarati , which is one of 22 Indian languages.
This is a Gujarati stemmer in Java. Stemming is a process in which affixes are removed form the root word (stem). It relates morphological variant words to corresponding common root. For example "પ્રતિઉપયોગી" is word which has stem " ઉપયોગ". Stemmers are language specific tools. The design of a stemming algorithm requires a significant level of linguistic expertise. There has been lot of significant work in the development and evaluation of stemmer for non-Indian languages, but very less or no significant work has been done on Indian front especially for Gujarati language.The code of this stemmer is based on algorithm designed under guidance of Prof. Nikita Desai, India. It takes input file of type .txt containing Gujarati text encoded as UTF-8 and then removes stop words which are unessential. After processing rest of the words, it outputs corresponding file containing all stem words plus other details. -
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Tipa2Unicode is a little stand-alone application which lets you input Tipa-shortcuts and then displays Unicode symbols. You can then paste either side of the conversion to LaTeX or a word processor.
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AraRooter
Find Arabic Root Word
Using Machine Learning, AraRooter finds the three-lettered root of any Arabic lemma with around 84% accuracy. -
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This project aimed at creating framework and binary data format for etymological Arabic system. and will not continue hosted at sourceforge because the term of use determine me as enemy, so I am prohibited from using sourceforge services.
