134 lines
9.5 KiB
Plaintext
134 lines
9.5 KiB
Plaintext
### Awesome Linguistics
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[](https://github.com/sindresorhus/awesome)
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A curated list of anything remotely related to linguistics, sorted in alphabetical order.
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- [Programming](#programming)
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- [Platforms and toolkits](#platforms-and-toolkits)
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- [Algorithms](#algorithms)
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- [Data sets](#data-sets)
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- [Resources](#resources)
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- [Deep learning models and transformers](#deep-learning-models-and-transformers)
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- [On Wikipedia](#on-wikipedia)
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- [On Youtube](#on-youtube)
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- [Books](#books)
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- [Free](#free)
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- [Non free](#non-free)
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- [Lists](#lists)
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- [Standards](#standards)
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- [Lists](#lists)
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- [Communities](#communities)
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### Programming
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*Libraries, frameworks and applications useful for developing applications.*
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### Platforms and toolkits
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* [CLARIN-D web tools](https://www.clarin-d.net/en/analysing) - Tools for Analysing Research Data
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* [CorpusExplorer](https://notes.jan-oliver-ruediger.de/software/corpusexplorer-overview/) - Software for corpus linguists and text/data mining enthusiasts. The CorpusExplorer combines over 50 interactive visualizations under a user-friendly interface.
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* [Haxe-linguistics](https://github.com/sexybiggetje/haxe-linguistics) - Early linguistical analysis and natural language processing library for Haxe.
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* [Natural](https://github.com/NaturalNode/natural) - General natural language tools for Node.js.
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* [Natural Language ToolKit (NLTK)](http://www.nltk.org/) - The most complete platform for building Python programs to work with human language data.
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* [Snowball](https://snowballstem.org/) - Snowball is a language in which stemming algorithms can be easily represented.
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* [Spacy](https://spacy.io/) - Industrial-strength National Language Processing in Python.
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* [Mate Tools](http://hdl.handle.net/11022/1007-0000-0000-8E4E-A), webservice via [WebLicht](https://weblicht.sfs.uni-tuebingen.de/)
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* [UBIAI](https://ubiai.tools/) - Easy-to-use text annotation tool for teams with most comprehensive auto-annotation features. Supports NER, relations and document classification as well as OCR annotation for invoice labeling.
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* [textblob-de](https://github.com/markuskiller/textblob-de) - Nice alternative for spacy (see above).
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* [UralicNLP](https://github.com/mikahama/uralicNLP) - An open source Python library for processing morphologically rich and, for the most part, endangered Uralic languages. It can do morphological analysis, generation, lemmatization, disambiguation and lexical lookup for a great many Uralic languages.
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### Algorithms
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* [Stemming algorithms for various European languages](http://snowball.tartarus.org/texts/stemmersoverview.html) - Various stemming algorithms from snowball.
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* [The Porter Stemmer Algorithm](http://tartarus.org/martin/PorterStemmer/) - The ‘official’ home page for distribution of the Porter Stemming Algorithm, written and maintained by its author, Martin Porter.
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### Data sets
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* [EuroRomCom Data](https://github.com/kirkins/euroromcom) - JSON formatted Pan-Romance word lists.
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* [Araneum Germanicum](http://aranea.juls.savba.sk/aranea_about/_germanicum.html)
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* [CEHugeWebCorpus](https://lindat.mff.cuni.cz/repository/xmlui/handle/11372/LRT-2638) - German corpus based on CommonCrawl
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* [Digitales Wörterbuch der deutschen Sprache (DWDS)](https://dwds.de)
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* [GC4 Corpus](https://german-nlp-group.github.io/projects/gc4-corpus.html) (CommonCrawl)
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* [IDS Corpora](https://www1.ids-mannheim.de/kl/projekte/korpora) - German Reference Corpus
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* [Leipzig Corpora Collection](https://wortschatz.uni-leipzig.de/en/download/) - sampled sentences in different languages.
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* [SdeWaC](https://www.ims.uni-stuttgart.de/forschung/ressourcen/korpora/sdewac.en.html) - big german internet corpus
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* [C-WEP](http://lingured.info/linguistic-resources/cwep/)
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* [DysList (list of dyslexic errors)](https://github.com/Rauschii/DysListGerman)
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* [Falko](https://www.linguistik.hu-berlin.de/de/institut/professuren/korpuslinguistik/forschung/falko)
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* [Litkey](https://www.linguistics.ruhr-uni-bochum.de/litkeycorpus/)
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* [OpinionSpam](https://github.com/hdaSprachtechnologie/OpinionSpam)
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### Resources
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* [How To Label Data](https://www.lighttag.io/how-to-label-data/) - Guide on managing large scale linguistic annotation projects.
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* [Low Resource Languages](https://github.com/RIchardLitt/low-resource-languages) - A list of resources for conservation, development, and documentation of low resource (human) languages.
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* [Language Science Press](https://langsci-press.org/) - Language Science Press is a born-digital scholar-led open access publisher in linguistics.
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### Deep learning models and transformers
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* [dbmdz BERT models](https://github.com/dbmdz/berts)
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* [Deepset German BERT model](https://deepset.ai/german-bert)
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* [Evaluating German Transformer Language Models with Syntactic Agreement Tests](https://github.com/DFKI-NLP/gevalm)
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* [German ELMo Model](https://github.com/t-systems-on-site-services-gmbh/german-elmo-model)
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* [german-transformer-training](https://github.com/PhilipMay/german-transformer-training)
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* [GermLM](https://github.com/tonianelope/Multilingual-BERT) (NER exploration)
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* [GerPT2](https://github.com/bminixhofer/gerpt2)
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* [Sentence Transformers](https://github.com/UKPLab/sentence-transformers)
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### On Wikipedia
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* [Bag of words model](https://en.wikipedia.org/wiki/Bag-of-words_model)
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* [Document classification](https://en.wikipedia.org/wiki/Document_classification)
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* [Language models](https://en.wikipedia.org/wiki/Language_model)
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* [Naive Bayes classification](https://en.wikipedia.org/wiki/Naive_Bayes_classifier)
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* [Natural language processing](https://en.wikipedia.org/wiki/Natural_language_processing)
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* [Outline of natural language processing](https://en.wikipedia.org/wiki/Outline_of_natural_language_processing)
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* [Parts of speech tagging](https://en.wikipedia.org/wiki/Part-of-speech_tagging)
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* [Sentiment analysis](https://en.wikipedia.org/wiki/Sentiment_analysis)
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* [Term frequency - inverse document frequency](https://en.wikipedia.org/wiki/Tf%E2%80%93idf)
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* [Vector space model](https://en.wikipedia.org/wiki/Vector_space_model)
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### On Youtube
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* [Computational Linguistics Lecture Playlist (Youtube)](https://www.youtube.com/playlist?list=PLegWUnz91WfuPebLI97-WueAP90JO-15i) - Lectures for University of Maryland class on computational linguistics.
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* [The Virtual Linguistics Campus](https://www.youtube.com/channel/UCaMpov1PPVXGcKYgwHjXB3g) - CC-licensed educational videos interconnected with Marburg University's e-learning platform of the same name.
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### Books
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*Some of the more interesting and complete books.*
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#### Free
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* [Essentials of Linguistics, 2nd edition](https://ecampusontario.pressbooks.pub/essentialsoflinguistics2/) - An introductory book (2nd edition).
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* [Introduction to Linguistics](https://linguistics.ucla.edu/people/Kracht/courses/ling20-fall07/ling-intro.pdf)
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* [Natural Language Processing with Python](https://www.nltk.org/book/) - The book from the NLTK package.
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* [Text Mining with R](https://www.tidytextmining.com)
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#### Non free
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* [Foundations of Computational Linguistics](https://books.google.com/books?id=o9iGAgAAQBAJ&dq=Foundations+of+Computational+Linguistics&hl=nl&source=gbs_navlinks_s)
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* [Foundations of Statistical Natural Language Processing](https://books.google.nl/books?id=YiFDxbEX3SUC)
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* [Semisupervised Learning for Computational Linguistics](https://books.google.com/books/about/Semisupervised_Learning_for_Computationa.html?id=VCd67cGB_rAC&redir_esc=y)
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* [Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition](https://books.google.nl/books?id=fZmj5UNK8AQC)
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* [The Oxford Handbook of Computational Linguistics](https://www.oxfordhandbooks.com/view/10.1093/oxfordhb/9780199276349.001.0001/oxfordhb-9780199276349)
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### Standards
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* [DTA Basisformat](https://www.deutschestextarchiv.de/doku/basisformat/)
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* [ISO TC 37 SC 4](https://www.iso.org/committee/297592.html)
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* [UIMA](https://docs.oasis-open.org/uima/v1.0/os/uima-spec-os.html)
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### Lists
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* [15 most popular books on good reads](https://www.goodreads.com/shelf/show/natural-language-processing)
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* GitHub topics [corpus-linguistics](https://github.com/topics/corpus-linguistics) & [nlp](https://github.com/topics/nlp)
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* [nlp-datasets](https://github.com/niderhoff/nlp-datasets)
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* [NLP-progress](https://github.com/sebastianruder/NLP-progress)
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* [/r/LanguageTechnology/](https://www.reddit.com/r/LanguageTechnology/)
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* [awesome-nlp](https://github.com/keon/awesome-nlp)
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* [Awesome Community-Curated NLP List](https://github.com/alvations/awesome-community-curated-nlp)
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* [awesome-chinese-nlp](https://github.com/crownpku/Awesome-Chinese-NLP)
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* [awesome-danish](https://github.com/fnielsen/awesome-danish)
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* [awesome-hungarian-nlp](https://github.com/oroszgy/awesome-hungarian-nlp)
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* [awesome Information Retrieval](https://github.com/harpribot/awesome-information-retrieval)
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* [Indonesian NLP](https://github.com/kmkurn/id-nlp-resource)
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* [Norwegian NLP resources](https://github.com/web64/norwegian-nlp-resources)
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* [German NLP resources](https://github.com/adbar/German-NLP/)
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* [awesome-nlp-polish](https://github.com/ksopyla/awesome-nlp-polish)
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* [awesome-spanish-nlp](https://github.com/dav009/awesome-spanish-nlp)
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* [M. Weisser's list of NLP/Computational Linguistics Resources](https://martinweisser.org/corpora_site/comp_ling_resources.html)
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* [NLP tools (Saarland University)](https://www.coli.uni-saarland.de/~csporled/page.php?id=tools)
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### Communities
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* [Linguistics Stack Exchange](https://linguistics.stackexchange.com/)
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* [Untranslatable.co, Multilingual urban dictionary](https://untranslatable.co/)
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