icu VS apertium

If you want graphemes, something lile libgrapheme might suit you. If just code points, then the utf8.h from ICU can work, but you can also roll your own if needed.

OP, is this money in the context of storing and counting money, or money in the context of internationalization and localization? For the latter, you probably want bindings to icu or the x/text/currency package.

https://github.com/unicode-org/icu/pull/2213

This affects all packages that have icu as a dependency, one of them being Node.js.

https://github.com/nodejs/node/issues/37271

I discovered this the hard way when some code malfunctioned shortly after daylight savings time kicked in.

No clue! It seems like a very deep rabbit hole to go down. You can start here: https://github.com/unicode-org/icu Version 72 I believe is when this was changed.

Installing icu4c from https://github.com/unicode-org/icu/releases/tag/release-71-1 and put the path in "--with-icu-lib"

wget https://github.com/unicode-org/icu/archive/release-58-3.tar.gz

You need something like icu. https://github.com/unicode-org/icu

ICU, which ships as part of the core internationalization and localization frameworks of every major operating system, has a facility for transliterating keyboards! This is how you can type in Roman characters and get Devanagari in text, or enter pinyin and get Han characters. You can compose a Hiragana to Latin transliteration — but it’s a stretch to get actual English words this way.

This is very cool, looking forward to it! I've been doing the same thing with Spanish Wikipedia articles for a while, using a few lines of Bash + Regex. I was using Apertium for it. https://apertium.org/ It's definitely worse than most ML-based solutions, but it works reliably and fast; you can run it entirely offline. With Spanish translations, the main problem I was facing is lack of vocabulary, so I created https://github.com/phil294/apertium-eng-spa-wiktionary which about doubles the amount of recognized words, albeit with wonky grammar.

I used to keep track of the state of machine translation some years back.

I think the way you measure the success of an automated translation is edit distance, i.e. how many manual edits you need to make to a translated text before you reach some acceptable state. I suppose it's somewhat subjective, but it is possible to construct a benchmark and allow for multiple correct results.

The best resources I knew back then were:

VISL's CG-3 self-reported a competitively low edit distance compared to Google Translate: https://visl.sdu.dk/constraint_grammar.html -- the abstraction unfortunately requires a rather deep knowledge of any one particular language's grammar. It is a convincing argument that in order to beat Google Translate, you want less fuzzy machine learning and more structural analysis. But you also need a PhD in computational linguistics and deep knowledge of each language.

Apertium has an open-source pipeline: https://apertium.org/ -- seems to be much more like an open-source approach with a quality similar to Google Translate (although I don't know if it's better or worse; probably slightly worse in most cases, and with a slightly lower coverage).

For context, I have been contributing CV Creole data to Unicode's CLDR and MediaWiki for a number of years now, but both are mostly manual work. I once considered setting up an Apertium language pair between CV Creole and Portuguese, given the grammatical similarities, but never got around to it.

Lingva is awesome. Also don't forget to check out LibreTranslate and Apertium. They are open source. Apertium can even translate web pages (you need to enter the URL).

#!/bin/bash set -x mkdir -p apertium-src && \ mkdir -p $MTDIR cd apertium-src && \ wget http://ftp.tsukuba.wide.ad.jp/software/gcc/releases/gcc-8.5.0/gcc-8.5.0.tar.gz -O - \ | gzip -dc \ | tar -xf - && \ cd gcc-8.5.0 && \ ./configure --prefix=$MTDIR --disable-multilib && \ make -j $(nproc) && \ make install && \ cd .. || exit 1 cd apertium-src && \ wget https://github.com/unicode-org/icu/releases/download/release-69-1/icu4c-69_1-src.tgz -O - \ | gzip -dc \ | tar -xf - \ && cd icu/source \ && CC=gcc CXX=g++ ./configure --prefix=$MTDIR \ && CC=gcc CXX=g++ make -j $(nproc) \ && CC=gcc CXX=g++ make install \ && cd ../.. \ || exit 1 cd apertium-src && \ svn checkout http://beta.visl.sdu.dk/svn/visl/tools/vislcg3/trunk vislcg3 && \ cd vislcg3 && ./get-boost.sh \ && ./cmake.sh -DCMAKE_INSTALL_PREFIX=$MTDIR \ -DICU_INCLUDE_DIR=$MTDIR/include \ -DICU_LIBRARY=$MTDIR/lib/libicuuc.so \ -DICU_IO_LIBRARY=$MTDIR/lib/libicuio.so \ -DICU_I18N_LIBRARY=$MTDIR/lib/libicui18n.so \ && make -j$(nproc) && \ make install && cd .. || exit 1 cd apertium-src && \ git clone https://github.com/apertium/lttoolbox && \ cd lttoolbox && ./autogen.sh --prefix=$MTDIR && make -j $(nproc) && make install && cd ../.. || exit 1 cd apertium-src && \ git clone https://github.com/apertium/apertium && \ cd apertium && ./autogen.sh --prefix=$MTDIR && make -j $(nproc) && make install && cd ../.. || exit 1 cd apertium-src && \ git clone https://github.com/apertium/apertium-lex-tools && \ cd apertium-lex-tools && ./autogen.sh --prefix=$MTDIR && make -j $(nproc) && make install && cd ../.. || exit 1 cd apertium-src && \ git clone https://github.com/apertium/apertium-tha && \ cd apertium-tha && ./autogen.sh --prefix=$MTDIR && make && make install && cd ../.. || exit 1 cd apertium-src && \ git clone https://github.com/apertium/apertium-tha-eng && \ cd apertium-tha-eng && ./autogen.sh --prefix=$MTDIR && make && make install && cd .. && \ cd .. || exit 1