libskk is a library to deal with Japanese kana-to-kanji conversion method.

This routine applies stemming algorithms to its parameters, returning the stemmed words as appropriate to the selected locale.

Mecab is a morphological analysis engine developed as a collaboration between the Kyoto university and Nippon Telegraph and Telephone Corporation. The engine is independent of any language, dictionary or corpus.

This module applies the Porter Stemming Algorithm to its parameters, returning the stemmed Russian (KOI8-R only) word.

Hime is an extremely easy-to-use input method framework. It is lightweight, stable, powerful and supports many commonly used input methods, including Cangjie, Zhuyin, Dayi, Ranked, Shrimp, Greek, Anthy, Korean, Latin, Random Cage Fighting Birds, Cool Music etc.

DParser is scannerless GLR parser generator. The form of the text to be parsed can be specified using a combination of regular expressions and grammar productions. Because of the parsing technique, a scannerless GLR parser based on the Tomita algorithm the grammar can be ambiguous, right or left recursive, have any number of null productions, and because there is no separate tokenizer, can include whitespace in terminals and have terminals which are prefixes of other terminals.

This module is a rather incomplete implementation of work done by Gudrun Putze-Meier.

This module implements a Portuguese stemming algorithm proposed in the paper A Stemming Algorithm for the Portuguese Language by Moreira, V. and Huyck, C.

Praat is a tool to perform phonetics tasks. It can do speech analysis (pitch, formant, intensity, ...), speech synthesis, labelling, segmenting and manipulation.

Lingua::Stem::Snowball::No is a perl port of the norwegian stemmer at http://snowball.tartarus.org.

Lingua::Stem::Snowball::Se is a perl port of the swedish stemmer at http://snowball.sourceforge.net.

This module applies the Porter Stemming Algorithm to its parameters, returning the stemmed Italian word.

This module converts English text into numbers. It supports both ordinal and cardinal numbers, negative numbers, and very large numbers.

UniDic for morphological analysis is a dictionary for analysis with the morphological analyser MeCab, where the short units exported from the database are used as entries (heading terms).

This module will tell you if a number, either in words or as digits, is a cardinal or ordinal number.

This package contains dictionary data derived from ipadic for use with MeCab.

The Link Grammar Parser is a syntactic parser of English, Russian, Arabic and Persian (and other languages as well), based on Link Grammar, an original theory of syntax and morphology. Given a sentence, the system assigns to it a syntactic structure, which consists of a set of labelled links connecting pairs of words. The parser also produces a "constituent" (HPSG style phrase tree) representation of a sentence (showing noun phrases, verb phrases, etc.).

Lingua::EN::Inflect provides plural inflections, "a"/"an" selection for English words, and manipulation of numbers as words. Plural forms of all nouns, most verbs, and some adjectives are provided. Where appropriate, "classical" variants (for example: "brother" -> "brethren", "dogma" -> "dogmata", etc.) are also provided.

Liblouis is a braille translator and back-translator named in honor of Louis Braille. It features support for computer and literary braille, supports contracted and uncontracted translation for many languages and has support for hyphenation. New languages can easily be added through tables that support a rule- or dictionary based approach. Tools for testing and debugging tables are also included. Liblouis also supports math braille, Nemeth and Marburg.

Lingua::Stem::Snowball::Da is a perl port of the danish stemmer at http://snowball.sourceforge.net, it was originally altered from the Lingua::Stem::Snowball::Se.

T1 is currently one of the best neural networks for Leela Chess Zero, however, it was superseded by the neural network T2.

This is an official neural network of a ``main run'' of the Leela Chess Zero project that was finished being trained in January of 2022.

Maia’s goal is to play the human move, not necessarily the best move. As a result, Maia has a more human-like style than previous engines, matching moves played by human players in online games over 50% of the time.

This is an official neural network of the Leela Chess Zero project that was finished being trained in April of 2022.