This module is a probability based, corpus-trained tagger that assigns part-of-speech tags to English text based on a lookup dictionary and a set of probability values. The tagger assigns appropriate tags based on conditional probabilities - it examines the preceding tag to determine the appropriate tag for the current word. Unknown words are classified according to word morphology or can be set to be treated as nouns or other parts of speech. The tagger also extracts as many nouns and noun phrases as it can, using a set of regular expressions.

This module attempts to pluralize or singularize short English phrases.

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

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.

Liblouisutdml is a library providing complete braille transcription services for xml, html and text documents. It translates into appropriate braille codes and formats according to its style sheet and the specifications in the document.

This module uses a modified version of the Porter Stemming Algorithm to return a stemmed French word.

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).

LibStemmer provides stemming library, supporting several languages.

Chewing is an intelligent phonetic (Zhuyin/Bopomofo) input method, one of the most popular choices for Traditional Chinese users.

This module extends the functionality of Lingua::EN::Inflect with three new functions for determining plurality of a word and forcefully converting a word to singular or plural.

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.).

This module provides a utility method, "to_identifier" for converting an arbitrary string into a readable representation using the ASCII subset of "\w" for use as an identifier in a computer program. The intent is to make unique identifier names from which the content of the original string can be easily inferred by a human just by reading the identifier.

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.

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.

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.

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

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

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 a smaller version of the T1 neural network, which is currently one of the best neural networks for Leela Chess Zero.

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.

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.

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.

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.