Difference between revisions of "Language/Multiple-languages/Culture/Text-Processing-Tools"

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If you don't know Python, please try this:
If you don't know Python, please try this:


<youtube>_uQrJ0TkZlc</youtube>
https://www.youtube.com/watch?v=_uQrJ0TkZlc


In progress.
In progress.
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== Diacritisation ==
== Diacritisation ==
In Arabic writing system, diacritics indicate the accents, but they are often omitted for writing fluently. The process of restoring diacritics is called diacritisation.
In Arabic writing system, diacritics indicate the accents, but they are often omitted for writing fluently. The process of restoring diacritics is called diacritisation.


Arabic:
Arabic:
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== Lemmatisation ==
== Lemmatisation ==
When you search a word in inflected form, your dictionary program can show you the result, during which the lemmatisation is done.
When you search a word in inflected form, the dictionary program can show you the result as lemma, during which the lemmatisation is done.


 
multiple languages:
Multiple languages:
* CST's lemmatiser https://www.cst.dk/online/lemmatiser/
* CST's lemmatiser https://www.cst.dk/online/lemmatiser/
* Natural Language Toolkit https://www.nltk.org/
* Pattern https://github.com/clips/pattern
* Pattern https://github.com/clips/pattern
* Simplemma https://github.com/adbar/simplemma
* TextBlob https://textblob.readthedocs.io/
* TextBlob https://textblob.readthedocs.io/
English:
* LemmInflect https://github.com/bjascob/LemmInflect
* Natural Language Toolkit https://www.nltk.org/
German:
* GermaLemma https://github.com/WZBSocialScienceCenter/germalemma
Hungarian:
* HuSpaCy https://github.com/huspacy/huspacy
Persian:
* Hazm https://github.com/roshan-research/hazm
Turkish:
* Zeyrek https://github.com/obulat/zeyrek


== Pitch-Accent Marking ==
== Pitch-Accent Marking ==
In Japanese and other languages, the pitch-accent is important on distinguishing different words. They are unwritten and required.
In Japanese and other languages, the pitch-accent is important on distinguishing different words. They are unwritten and required.


Japanese:
Japanese:
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* tdmelodic https://github.com/PKSHATechnology-Research/tdmelodic
* tdmelodic https://github.com/PKSHATechnology-Research/tdmelodic


== Stress Generation ==
== Stress Marking ==
In Russian and other languages, the stress is important on distinguishing different words. They are usually omitted.
In Russian and other languages, the stress is important on distinguishing different words. They are usually omitted.


Russian:
Russian:
* RussianGram https://russiangram.com/
* RussianGram https://russiangram.com/
* Russian Stress Finder https://www.readyrussian.org/WebApps/StressFinder/
* Russian Stress Finder https://www.readyrussian.org/WebApps/StressFinder/
== Transcription ==
Some languages are written in more than one writing systems. This tool converts them from one to another.
Chinese:
* Chinese-Tools.com https://www.chinese-tools.com/tools/converter-simptrad.html
* ChineseConverter.com https://www.chineseconverter.com/en/convert/simplified-to-traditional
* hanzi2reading https://github.com/bdon/hanzi2reading
* OMGChinese.com https://www.omgchinese.com/tools/chinese-simplified-traditional-converter
== Part of Speech Tagging ==
It tags words in the sentence with parts of speech. Some of them can draw parse trees.
Multiple languages:
* CoreNLP https://github.com/stanfordnlp/CoreNLP
* Natural Language Toolkit https://www.nltk.org/
* spaCy https://spacy.io/
* Stanford Log-linear Part-Of-Speech Tagger https://nlp.stanford.edu/software/tagger.shtml
Arabic:
* Arabycia https://github.com/mohabmes/Arabycia
Chinese:
* FoolNLTK https://github.com/rockyzhengwu/FoolNLTK
* FudanNLP https://github.com/FudanNLP/fnlp
* HanLP https://github.com/hankcs/HanLP
* LAC https://github.com/baidu/lac
* LTP https://github.com/HIT-SCIR/ltp
* SnowNLP https://github.com/isnowfy/snownlp
* pkuseg https://github.com/lancopku/pkuseg-python
* pyhanlp https://github.com/hankcs/pyhanlp
* THULAC https://github.com/thunlp/THULAC-Python
Japanese:
* janome https://github.com/mocobeta/janome
* Juman++ https://github.com/ku-nlp/jumanpp
* Kagome https://github.com/ikawaha/kagome
* Kuromoji https://github.com/atilika/kuromoji / https://github.com/takuyaa/kuromoji.js/
* KyTea http://www.phontron.com/kytea/
* MeCab https://taku910.github.io/mecab/
* nagisa https://github.com/taishi-i/nagisa
* Sudachi https://github.com/WorksApplications/Sudachi / https://github.com/WorksApplications/SudachiPy
Thai:
* PyThaiNLP https://github.com/PyThaiNLP/pythainlp
* SynThai https://github.com/KrakenAI/SynThai
* TLTK https://pypi.org/project/tltk/
Vietnamese:
* JVnSegmenter http://jvnsegmenter.sourceforge.net/
* VnCoreNLP https://github.com/vncorenlp/VnCoreNLP
== Romanisation ==
multiple languages:
* Translit https://translit.cc/
Iranian Persian:
* Behnevis: easy farsi transliteration (pinglish) editor https://behnevis.com/en/
Japanese:
* NihongoDera - Romaji Converter https://nihongodera.com/tools/romaji-converter
Korean:
* 한국어/로마자 변환기 http://roman.cs.pusan.ac.kr/
Mandarin Chinese:
* Chinese Romanization Converter https://chinese.gratis/tools/zhuyin/
Standard Arabic:
* Romanize Arabic ALA-LC http://romanize-arabic.camel-lab.com/
Thai:
* thai-language.com Romanize an Arbitrary Thai Word http://thai-language.com/?nav=dictionary&anyxlit=1
* Phonetic transliteration of Thai https://www.thailit.com/transliterate.php


== Word Segmentation ==
== Word Segmentation ==
In some languages, words are not separated by spaces, for example: Chinese, Japanese, Lao, Thai. In Vietnamese, spaces are used to divide syllables instead of words. This brings about difficulties for computer programs like [https://vocabhunter.github.io/ VocabHunter], [https://github.com/jeffkowalski/gritz gritz] and [https://github.com/zg/text-memorize text-memorize], where words are detected only with spaces.
In some languages, words are not separated by spaces, for example: Chinese, Japanese, Khmer, Lao, Thai. In Vietnamese, spaces are used to divide syllables instead of words. This brings about difficulties for computer programs like [https://vocabhunter.github.io/ VocabHunter], [https://github.com/jeffkowalski/gritz gritz] and [https://github.com/zg/text-memorize text-memorize], where words are detected only with spaces.
 
The solution is called “[https://en.wikipedia.org/wiki/Text_segmentation#Word_segmentation word segmentation]”, which detects words and insert spaces in between or put the segmented words into a list.


The solution is called “[https://en.wikipedia.org/wiki/Text_segmentation#Word_segmentation word segmentation]”, which detects words and insert spaces in between or put the segmented words into a list. You may want to ask: The programs only recognise spaces as the word separators, how to deal with Vietnamese? The answer is using the [https://en.wikipedia.org/wiki/Non-breaking_space non-breaking space].
Burmese, Khmer, Lao, Thai:
* Chamkho https://codeberg.org/mekong-lang/chamkho


Burmese:
* Myan-word-breaker https://github.com/stevenay/myan-word-breaker


Chinese:
Chinese:
* Ansj https://github.com/NLPchina/ansj_seg
* Ansj https://github.com/NLPchina/ansj_seg
* CoreNLP https://github.com/stanfordnlp/CoreNLP
* FoolNLTK https://github.com/rockyzhengwu/FoolNLTK
* FoolNLTK https://github.com/rockyzhengwu/FoolNLTK
* FudanNLP https://github.com/FudanNLP/fnlp
* FudanNLP https://github.com/FudanNLP/fnlp
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* DongDu https://github.com/rockkhuya/DongDu
* DongDu https://github.com/rockkhuya/DongDu
* JVnSegmenter http://jvnsegmenter.sourceforge.net/
* JVnSegmenter http://jvnsegmenter.sourceforge.net/
* Roy_VnTokenizer https://github.com/roy-a/Roy_VnTokenizer
* VietSeg https://github.com/manhtai/vietseg
* VietSeg https://github.com/manhtai/vietseg
* VnCoreNLP https://github.com/vncorenlp/VnCoreNLP
* VnCoreNLP https://github.com/vncorenlp/VnCoreNLP
==Other Lessons==
* [[Language/Multiple-languages/Culture/Internet-Dictionaries|Internet Dictionaries]]
* [[Language/Multiple-languages/Culture/Astrology-in-different-Cultures-and-Languages|Astrology in different Cultures and Languages]]
* [[Language/Multiple-languages/Culture/How-to-make-a-TSV-file|How to make a TSV file]]
* [[Language/Multiple-languages/Culture/Texts-and-Audios-under-a-Public-License|Texts and Audios under a Public License]]
* [[Language/Multiple-languages/Culture/Calendar-and-Clock|Calendar and Clock]]
* [[Language/Multiple-languages/Culture/Online-Specialized-Dictionaries|Online Specialized Dictionaries]]
* [[Language/Multiple-languages/Culture/Similar-Sayings|Similar Sayings]]
* [[Language/Multiple-languages/Culture/Elements-of-Traditional-Architectures:-Western-Europe|Elements of Traditional Architectures: Western Europe]]
* [[Language/Multiple-languages/Culture/Helpful-Anki-Shared-Decks|Helpful Anki Shared Decks]]
* [[Language/Multiple-languages/Culture/Internet-resources-for-learning-specific-languages|Internet resources for learning specific languages]]
<span links></span>

Latest revision as of 13:50, 16 February 2024

Multiple-languages-flag-polyglotclub.jpg

In this lesson, several useful linguistic tools useful for common language learners are discussed. They are not always accurate, so keep in mind.

Many of the tools introduced are written in Python, which is an important language in machine learning and easy to learn.

If you don't know Python, please try this:

https://www.youtube.com/watch?v=_uQrJ0TkZlc

In progress.

Diacritisation[edit | edit source]

In Arabic writing system, diacritics indicate the accents, but they are often omitted for writing fluently. The process of restoring diacritics is called diacritisation.

Arabic:

Lemmatisation[edit | edit source]

When you search a word in inflected form, the dictionary program can show you the result as lemma, during which the lemmatisation is done.

multiple languages:

English:

German:

Hungarian:

Persian:

Turkish:

Pitch-Accent Marking[edit | edit source]

In Japanese and other languages, the pitch-accent is important on distinguishing different words. They are unwritten and required.

Japanese:

Stress Marking[edit | edit source]

In Russian and other languages, the stress is important on distinguishing different words. They are usually omitted.

Russian:

Transcription[edit | edit source]

Some languages are written in more than one writing systems. This tool converts them from one to another.

Chinese:

Part of Speech Tagging[edit | edit source]

It tags words in the sentence with parts of speech. Some of them can draw parse trees.

Multiple languages:

Arabic:

Chinese:

Japanese:

Thai:

Vietnamese:

Romanisation[edit | edit source]

multiple languages:

Iranian Persian:

Japanese:

Korean:

Mandarin Chinese:

Standard Arabic:

Thai:

Word Segmentation[edit | edit source]

In some languages, words are not separated by spaces, for example: Chinese, Japanese, Khmer, Lao, Thai. In Vietnamese, spaces are used to divide syllables instead of words. This brings about difficulties for computer programs like VocabHunter, gritz and text-memorize, where words are detected only with spaces.

The solution is called “word segmentation”, which detects words and insert spaces in between or put the segmented words into a list.

Burmese, Khmer, Lao, Thai:

Burmese:

Chinese:

Japanese:

Lao:

Thai:

Vietnamese:

Other Lessons[edit | edit source]

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