Difference between revisions of "Ideas for Google Summer of Code"

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This is the ideas page for [[Google Summer of Code]], here you can find ideas on interesting projects that would make Apertium more useful for people and improve or expand our functionality. If you have an idea please add it below, if you think you could mentor someone in a particular area, add your name to "Interested mentors" using <nowiki>~~~</nowiki>
This is the ideas page for [[Google Summer of Code]], here you can find ideas on interesting projects that would make Apertium more useful for people and improve or expand our functionality.


'''Current Apertium contributors''': If you have an idea please add it below, if you think you could mentor someone in a particular area, add your name to "Interested mentors" using <code><nowiki>~~~</nowiki></code>.
The page is intended as an overview of the kind of projects we have in mind. If one of them particularly piques your interest, please come and discuss with us on <code>#apertium</code> on <code>irc.freenode.net</code>, mail the [[Contact|mailing list]], or draw attention to yourself in some other way.


'''Prospective GSoC contributors''': The page is intended as an overview of the kind of projects we have in mind. If one of them particularly piques your interest, please come and discuss with us on <code>#apertium</code> on <code>irc.oftc.net</code> ([[IRC|more on IRC]]), mail the [[Contact|mailing list]], or draw attention to yourself in some other way.
Note that, if you have an idea that isn't mentioned here, we would be very interested to hear about it.

Note that if you have an idea that isn't mentioned here, we would be very interested to hear about it.


Here are some more things you could look at:
Here are some more things you could look at:


* [[Top tips for GSOC applications]]
* the [http://bugs.apertium.org/cgi-bin/bugzilla/buglist.cgi?cmdtype=runnamed&namedcmd=Open%20Bugs open bugs] page on Bugzilla
* Get in contact with one of our long-serving [[List of Apertium mentors|mentors]] &mdash; they are nice, honest!
* pages in the [[:Category:Development|development category]]
* Pages in the [[:Category:Development|development category]]
* resources that could be converted or expanded in the [[incubator]].
* Resources that could be converted or expanded in the [[incubator]]. Consider doing or improving a language pair (see [[incubator]], [[nursery]] and [[staging]] for pairs that need work)
* Unhammer's [[User:Unhammer/wishlist|wishlist]]
* Unhammer's [[User:Unhammer/wishlist|wishlist]]
<!--* The open issues [https://github.com/search?q=org%3Aapertium&state=open&type=Issues on Github] - especially the [https://github.com/search?q=org%3Aapertium+label%3A%22good+first+issue%22&state=open&type=Issues Good First Issues]. -->


__TOC__
<!--
See the list sorted by: {{comment|Do we need this? - [[User:Francis Tyers|Francis Tyers]]}}


If you're a prospective GSoC contributor trying to propose a topic, the recommended way is to request a wiki account and then go to <pre>http://wiki.apertium.org/wiki/User:[[your username]]/GSoC2023Proposal</pre> and click the "create" button near the top of the page. It's also nice to include <code><nowiki>[[</nowiki>[[:Category:GSoC_2023_student_proposals|Category:GSoC_2023_student_proposals]]<nowiki>]]</nowiki></code> to help organize submitted proposals.
* [[/Difficulty|difficulty level]],
* [[/Thematic|theme]]
-->
==List==


== Language Data ==
''Note: The table below is sortable by column. Click on the little squares below or next to the headers.''


Can you read or write a language other than English (and we do mean any language)? If so, you can help with one of these and we can help you figure out the technical parts.
{|class="wikitable sortable"
! Task !! Difficulty !! Description !! Rationale !! Requirements !! Interested<br/>mentors
|-
| '''Morphology with HFST (and Foma)''' <small>[[/Morphology with HFST|read more...]]</small> || 3.&nbsp;Medium || Modify the Helsinki Finite State Toolkit to work nicely with Apertium (the [[Apertium stream format]], [[Superblanks]] etc.). That will involve implementing the tokenise-as-you-analyse algorithm as presented in this paper.<ref>Alicia Garrido-Alenda, Mikel L. Forcada, Rafael C. Carrasco (2002) [http://www.dlsi.ua.es/~mlf/docum/garrido02p.pdf Incremental construction and maintenance of morphological analysers based on augmented letter transducers]</ref> For bonus points, do the same for [[Foma]]. || The Helsinki Finite State Toolkit provides a drop-in replacement for the Xerox <code>lexc</code> and <code>twol</code> formalisms. There are many morphological analysers/generators "in the wild" written in these formalisms, and they provide substantial features for dealing with morphologically complex languages. || C++, Knowledge of FSTs || [[User:Francis Tyers|Francis Tyers]], [[User:TommiPirinen|Tommi Pirinen]]
|-
| '''Java port of Apertium runtime''' || 3.&nbsp;Medium || We have a Java version of 3/4 of the core elements of Apertium. Do the rest and integrate. This consists mainly of porting the HMM [[tagger]] (some parts have already been ported, HMM and loading of data is incomplete and untested). You can read more on: [[Java port of Apertium runtime]] || A "Java port" of Apertium would enable use on J2ME/Android phones, web pages (applets), desktop application, Java server applications. || Java (reading C++ code required) || [[User:Jacob Nordfalk|Jacob Nordfalk]], [[User:Jimregan|Jimregan]]
|-
| '''Easy dictionary maintenance''' <small>[[/Easy dictionary maintenance|read more...]]</small> || 2.&nbsp;Hard || Write code that simplifies the maintenance of the single-word part of Apertium monolingual and bilingual dictionaries. || Apertium dictionaries are very heterogeneous, but a great part of the development of a language pair consists in adding single words to monolingual and bilingual dictionaries, and, indeed, work on this part of the dictionaries is crucial for coverage and usefulness. Currently, dictionary maintenance is difficult because it involves editing an XML file. This may be slowing down the development of many language pairs. || Knowledge of XML, XSLT and one programming language that allows XML processing and easy writing of a user interface. The task may involve building an application that (a) parses and reads the open-class (noun, adjective, verb) single-word part of the dictionary amenable to simple, data-base-like treatment, saving the remaining (hard to treat) part of the dictionaries, (b) allows the user to easily add words (together with their inflection paradigms) through a friendly user interface and (c) then combines the extended single-word data with the remaining data into Apertium monolingual and bilingual dictionaries ready to be compiled. Ideas and code from Apertium-dixtools could be useful.
|| [[User:Mlforcada|Mlforcada]], [[User:Jimregan|Jimregan]], [[User:Jacob Nordfalk|Jacob Nordfalk]], [[User:Japerez|Japerez]]
|-
| '''Discontiguous multiwords''' <small>[[/Discontiguous multiwords|read more...]]</small> || 3.&nbsp;Medium || The task will be to develop, or adapt a module to deal with these kind of contiguous multiword expressions, for example, taking 'liggja ekki fyrir' and reordering it as 'liggja# fyrir ekki'. || In many languages, such as English, Norwegian and Icelandic, there are discontiguous multiwords, e.g. phrasal verbs, that we cannot easily support. For example 'liggja ekki fyrir' in Icelandic should be translated in English as 'to be not clear', but we cannot have 'liggja fyrir' as a traditional multiword because of the extra 'adverb', or it could even be a whole NP. || C++, Knowledge of FSTs || [[User:Francis Tyers|Francis Tyers]], [[User:Jimregan|Jimregan]]
|-
| '''Flag diacritics in lttoolbox''' <small>[[/Flag diacritics in lttoolbox|read more...]]</small> || 2.&nbsp;Hard || Adapt [[lttoolbox]] to elegantly use flag diacritics. Flag diacritics are a way of avoiding transducer size blow-up by discarding impossible paths at runtime as opposed to compile time. || This will involve designing some changes to our XML dictionary format (see [[lttoolbox]], and implementing the associated changes in the FST compiling processing code. The reason behind this is that many languages have prefix inflection, and we cannot currently deal with this without either making paradigms useless, or overanalysing (e.g. returning analyses where none exist). Flag diacritics (or constraints) would allow us to restrict overanalysis without blowing up the size of our dictionaries. || C++, XML, Knowledge of FSTs || [[User:Francis Tyers|Francis Tyers]], [[User:Jacob Nordfalk|Jacob Nordfalk]]
|-
| '''Flag diacritics in lttoolbox-java''' <small>[[/Flag diacritics in lttoolbox|read more...]]</small> || 2.&nbsp;Hard || Adapt [[lttoolbox-java]] to elegantly use flag diacritics. Flag diacritics are a way of avoiding transducer size blow-up by discarding impossible paths at runtime as opposed to compile time. || This will involve designing some changes to our XML dictionary format (see [[lttoolbox]], and implementing the associated changes in the FST compiling processing code. The reason behind this is that many languages have prefix inflection, and we cannot currently deal with this without either making paradigms useless, or overanalysing (e.g. returning analyses where none exist). Flag diacritics (or constraints) would allow us to restrict overanalysis without blowing up the size of our dictionaries. || Java, XML, Knowledge of FSTs || [[User:Jacob Nordfalk|Jacob Nordfalk]]
|-
| '''Linguistically-driven bilingual-phrase filtering for inferring transfer rules''' || 3.&nbsp;Medium || Re-working apertium-transfer-training-tools to filter the set of bilingual phrases automatically obtained from a word-aligned sentence pair by using linguistic criteria. || Apertium-transfer-training-tools is a cool piece of software that generates shallow-transfer rules from aligned parallel corpora. It could greatly speed up the creation of new language pairs by generating rules that would otherwise have to be written by human linguists || C++, general knowledge of GIZA++, Perl considered a plus. || [[User:Jimregan|Jimregan]]
|-
| '''Context-dependent lexicalised categories for inferring transfer rules''' || 2.&nbsp;Hard || Re-working apertium-transfer-training-tools to use context-dependent lexicalised categories in the inference of shallow-transfer rules. || Apertium-transfer-training-tools generates shallow-transfer rules from aligned parallel corpora. It uses an small set of lexicalised categories, categories that are usually involved in lexical changes, such as prepositions, pronouns or auxiliary verbs. Lexicalised categories differentiate from the rest of categories because their lemmas are taken into account in the generation of rules. || C++, general knowledge of GIZA++, XML. || [[User:Jimregan|Jimregan]]
|-
| '''Improve integration of'''<br/>'''lttoolbox in libvoikko''' <small>[[/Improve integration of lttoolbox in libvoikko|read more...]]</small> || 3.&nbsp;Medium || Dictionaries from [[lttoolbox]] can now be used for spellchecking directly with [[libvoikko]] (see [[Spell checking]]). The idea of this project is to improve the integration. Fix bugs, look at ways of codifying "standard"/"sub-standard" forms in our dictionaries. || Spell checkers can be useful, for languages other than English moreso. They are one of the "must have" items of language technology. If we can re-use Apertium data for this purpose it will help both the project (by making creating new language pairs more rewarding) and the language communities (by making more useful software). || XML, C++. || [[User:Francis Tyers|Francis Tyers]]
|-
| '''Complex multiwords''' || 2.&nbsp;Hard || Write a bidirectional module for specifying complex multiword units, for example ''dirección general'' and ''zračna luka''. See ''[[Multiwords]]'' for more information. || Although in the Romance languages it is not a big problem, as soon as you start to get to languages with cases (e.g. Serbo-Croatian, Slovenian, German, etc.) the problem comes that you can't define a multiword of <code>adj nom</code> because the adjective has a lot of inflection. || Java or C++, XML || [[User:Jimregan|Jimregan]]
|-
| '''Adopt a'''<br/>'''language pair''' <small>[[/Adopt a language pair|read more...]]</small> || 4.&nbsp;Entry&nbsp;level || Take on an orphaned language pair, and bring it up to release quality results. What this quality will be will depend on the language pair adopted, and will need to be discussed with the prospective mentor. This will involve writing linguistic data (including morphological rules and transfer rules &mdash; which are specified in a declarative language) || Apertium has a few pairs of languages (e.g. sh-mk, en-af, ga-gd, etc...) that are orphaned, they don't have active maintainers. A lot of these pairs have a lot of work already put in, just need another few months to get them to release quality. See also [[Incubator]]|| XML, a scripting language (Python, Perl), good knowledge of the language pair adopted. || [[User:Francis Tyers|Francis Tyers]], [[User:Jimregan|Jimregan]], [[User:Kevin Scannell|Kevin&nbsp;Scannell]], [[User:Trondtr|Trondtr]], [[User:Niunniminuni|Niunniminuni]], [[User:Unhammer|Unhammer]]
|-
| '''Post-edition '''<br/>'''tool''' || 3.&nbsp;Medium || Make a post-edition tool to speed up revision of Apertium translations. It would likely include at least support for spelling and grammar checking, along with defining user-specified rules for fixing translations (search and replace, etc.). This tool can reuse an existing grammar checker such as [http://www.languagetool.org LanguageTool]. || After translating with Apertium revision work has to be done to consider a translation as an "adequate" translation. An intelligent post-edition environment will help doing this task. In this environment some typical mistakes in the translation process that can be automatically detected (for example unknown words and homographs) could be highlighted to be taken in consideration while doing post-edition. Some typical mistakes could also be defined to advise the post-editor to check them. The application could be more useful if it is built as a web application. || XML, PHP, Python, Java, C, C++, whichever programming language, platforms for building web applications. || [[User:Japerez|Japerez]], [[User:Jimregan|Jimregan]], [[User:villarejo|villarejo]]
|-
| '''Detect 'hidden' unknown words''' <small>[[/Detect hidden unknown words|read more...]]</small>|| 3.&nbsp;Medium || The part-of-speech tagger of Apertium can be modified to work out the likelihood of each 'tag' in a certain context, this can be used to detect missing entries in the dictionary. || Apertium dictionaries may have incomplete entries, that is, surface forms (lexical units as they appear in running texts) for which the dictionary does not provided all the possible lexical forms (consisting of lemma, part-of-speech and morphological inflection information). As those surface form for which there is at least one lexical form cannot be considered unknown words, it is difficult to know whether all lexical forms for a given surface form have been included in the dictionaries or not. This feature will detect 'possible' missing lexical forms for those surface forms in the dictionaries. || C++ if you plan to modify the part-of-speech tagger; whatever if rewriting it from scratch. || [[User:Fsanchez|Felipe Sánchez-Martínez]]
|-
| '''Format filters''' || 4.&nbsp;Entry&nbsp;level || Making apertium capable of dealing with more different formats, for the minimum: files marked up with LaTeX and MediaWiki. || Apertium can currently deal with texts in plain-text, RTF, HTML and ODT formats by means of a format definition file. It should be easy to use the same language to define filters for other formats. || Apertium format definition language and/or scripting languages. || [[User:Villarejo|Villarejo]]
|-
| '''Geriaoueg<br/>vocabulary assistant''' || 4.&nbsp;Entry&nbsp;level || Extend [[Geriaoueg]] so that it works more reliably with broken HTML and with any given language pair. || [[Geriaoueg]] is a program that provides "popup" vocabulary assistance, something like BBC Vocab or Lingro. Currently it only works with Breton--French, Welsh--English and Spanish--Breton. This task would be to develop it to work with any language in our SVN and fix problems with processing and displaying non-standard HTML. || PHP, C++, XML || [[User:Francis Tyers|Francis Tyers]]
|-
| '''Corpus-assisted dictionary expansion''' || 4.&nbsp;Entry&nbsp;level || Semi-automatic bilingual word equivalence retrieval from a bitext and a monolingual word list. || Improve an existing Python script to retrieve the best translations (suggestions) of a word (typically an unknown word) given a particular parallel text corpus. Perhaps combine the result with automatic paradigm guessing (also suggestions) to improve the productivity of the lexical work for most contributors|| Python, C/C++, AWK, Bash, perhaps web interface in PHP, Python, Ruby on Rails || [[User:Sortiz|Sortiz]], [[User:Jimregan|Jimregan]], [[User:Villarejo|Villarejo]]
|-
| '''Improvements to target-language tagger training''' <small>[[/Improvements to target-language tagger training|read more...]]</small> || 2.&nbsp;Hard || Modify apertium-tagger-training-tools so that it can deals with n-stage transfer rules when segmenting the input source-language text, and applies a k-best viterbi pruning approach that does not require to compute the a-priori likelihood of every disambiguation path before pruning. || apertium-tagger-training-tools is a program for doing [[target-language tagger training]], meaning it improves POS tagging performance specifically for the translation task, achieving a result for unsupervised training comparable with supervised training. This task would also require switching the default perl-based language model to either IRSTLM or RandLM (or both!). || C++, XML, XSLT || [[User:Fsanchez|Felipe Sánchez-Martínez]]
|-
| '''Accent and diacritic'''<br/>'''restoration''' <small>[[/Automatic diacritic restoration|read more...]]</small> || 3.&nbsp;Medium || Create an optional module to restore diacritics and accents on input text, and integrate it into the Apertium pipeline. || Many languages use diacritics and accents in normal writing, and Apertium is designed to use these, however in some places, especially for example. instant messaging, irc, searching in the web etc. these are often not used or untyped. This causes problems as for the engine, ''traduccion'' is not the same as ''traducción''. || C, C++, XML, familiarity with linguistic issues || [[User:Kevin Scannell|Kevin&nbsp;Scannell]]
|-
| '''VM for the transfer module''' <small>[[/VM for transfer|read more...]]</small> || 3.&nbsp;Medium || VM for the current transfer architecture of Apertium and for the future transfers, pure C++ || Define an instruction set for a virtual machine that processes transfer code, then implement a prototype in Python, then porting to C++. The rationale behind this is that XML tree-walking is quite slow and CPU intensive. In modern (3 or more stage) pairs, transfer takes up most of the CPU. There are other options, like [[Bytecode for transfer]], but we would like something that does not require external libraries and is adapted specifically for Apertium. || Python, C/C++, XML, XSLT, code optimisation, JIT techniques, etc. || [[User:Sortiz|Sortiz]]
|
|-
| '''Hybrid MT''' || 2. Hard || Building Apertium-[http://www.openmatrex.org/marclator/marclator.html Marclator] rule-based/corpus-based hybrids || Both the rule-based machine translation system Apertium and the corpus-based machine translation system [http://www.openmatrex.org/marclator/marclator.html Marclator] do some kind of chunking of the input as well as use a relatively straightforward left-to-right machine translation strategy. This has been explored [http://www.dlsi.ua.es/~fsanchez/pub/pdf/sanchez-martinez09d.pdf before] but there are other ways to organize hybridization which should be explored (the mentor is haopy to discuss). Hybridization may make it easier to adapt Apertium to a particular corpus by using chunk pairs derived from it. || Knowledge of Java, C++, and scripting languages, and appreciation for research-like coding projects || [[User:Mlforcada|Mlforcada]], [[User:Jimregan|Jimregan]]
|}


{{IdeaSummary
==Notes==
| name = Develop a morphological analyser
<references/>
| difficulty = easy
==Further reading==
| size = either
| skills = XML or HFST or lexd
| description = Write a morphological analyser and generator for a language that does not yet have one
| rationale = A key part of an Apertium machine translation system is a morphological analyser and generator. The objective of this task is to create an analyser for a language that does not yet have one.
| mentors = [[User:Francis Tyers|Francis Tyers]], [[User:Firespeaker|Jonathan Washington]], [[User: Sevilay Bayatlı|Sevilay Bayatlı]], Hossep, nlhowell, [[User:Popcorndude]]
| more = /Morphological analyser
}}

{{IdeaSummary
| name = apertium-separable language-pair integration
| difficulty = Medium
| size = small
| skills = XML, a scripting language (Python, Perl), some knowledge of linguistics and/or at least one relevant natural language
| description = Choose a language you can identify as having a good number of "multiwords" in the lexicon. Modify all language pairs in Apertium to use the [[Apertium-separable]] module to process the multiwords, and clean up the dictionaries accordingly.
| rationale = Apertium-separable is a newish module to process lexical items with discontinguous dependencies, an area where Apertium has traditionally fallen short. Despite all the module has to offer, many translation pairs still don't use it.
| mentors = [[User:Firespeaker|Jonathan Washington]], [[User:Popcorndude]]
| more = /Apertium separable
}}

{{IdeaSummary
| name = Bring an unreleased translation pair to releasable quality
| difficulty = Medium
| size = large
| skills = shell scripting
| description = Take an unstable language pair and improve its quality, focusing on testvoc
| rationale = Many Apertium language pairs have large dictionaries and have otherwise seen much development, but are not of releasable quality. The point of this project would be bring one translation pair to releasable quality. This would entail obtaining good naïve coverage and a clean [[testvoc]].
| mentors = [[User:Firespeaker|Jonathan Washington]], [[User:Seviay Bayatlı|Sevilay Bayatlı]], [[User:Unhammer]], [[User:hectoralos|Hèctor Alòs i Font]]
| more = /Make a language pair state-of-the-art
}}

{{IdeaSummary
| name = Develop a prototype MT system for a strategic language pair
| difficulty = Medium
| size = large
| skills = XML, some knowledge of linguistics and of one relevant natural language
| description = Create a translation pair based on two existing language modules, focusing on the dictionary and structural transfer
| rationale = Choose a strategic set of languages to develop an MT system for, such that you know the target language well and morphological transducers for each language are part of Apertium. Develop an Apertium MT system by focusing on writing a bilingual dictionary and structural transfer rules. Expanding the transducers and disambiguation, and writing lexical selection rules and multiword sequences may also be part of the work. The pair may be an existing prototype, but if it's a heavily developed but unreleased pair, consider applying for "Bring an unreleased translation pair to releasable quality" instead.
| mentors = [[User:Firespeaker|Jonathan Washington]], [[User:Sevilay Bayatlı| Sevilay Bayatlı]], [[User:Unhammer]], [[User:hectoralos|Hèctor Alòs i Font]]
| more = /Adopt a language pair
}}

{{IdeaSummary
| name = Add a new variety to an existing language
| difficulty = easy
| size = either
| skills = XML, some knowledge of linguistics and of one relevant natural language
| description = Add a language variety to one or more released pairs, focusing on the dictionary and lexical selection
| rationale = Take a released language, and define a new language variety for it: e.g. Quebec French or Provençal Occitan. Then add the new variety to one or more released language pairs, without diminishing the quality of the pre-existing variety(ies). The objective is to facilitate the generation of varieties for languages with a weak standardisation and/or pluricentric languages.
| mentors = [[User:hectoralos|Hèctor Alòs i Font]], [[User:Firespeaker|Jonathan Washington]],[[User:piraye|Sevilaybayatlı]]
| more = /Add a new variety to an existing language
}}

{{IdeaSummary
| name = Leverage and integrate language preferences into language pairs
| difficulty = easy
| size = medium
| skills = XML, some knowledge of linguistics and of one relevant natural language
| description = Update language pairs with lexical and orthographical variations to leverage the new [[Dialectal_or_standard_variation|preferences]] functionality
| rationale = Currently, preferences are implemented via language variant, which relies on multiple dictionaries, increasing compilation time exponentially every time a new preference gets introduced.
| mentors = [[User:Xavivars|Xavi Ivars]] [[User:Unhammer]]
| more = /Use preferences in pair
}}

{{IdeaSummary
| name = Add Capitalization Handling Module to a Language Pair
| difficulty = easy
| size = small
| skills = XML, knowledge of some relevant natural language
| description = Update a language pair to make use make use of the new [[Capitalization_restoration|Capitalization handling module]]
| rationale = Correcting capitalization via transfer rules is tedious and error prone, but putting them in a separate set of rules should allow them to be handled in a more concise and maintainable way. Additionally, it is possible that capitalization rule could be moved to monolingual modules, thus reducing development effort on translators.
| mentors = [[User:Popcorndude]]
| more = /Capitalization
}}

== Data Extraction ==

A lot of the language data we need to make our analyzers and translators work already exists in other forms and we just need to figure out how to convert it. If you know of another source of data that isn't listed, we'd love to hear about it.

{{IdeaSummary
| name = dictionary induction from wikis
| difficulty = Medium
| size = either
| skills = MySQL, mediawiki syntax, perl, maybe C++ or Java; Java, Scala, RDF, and DBpedia to use DBpedia extraction
| description = Extract dictionaries from linguistic wikis
| rationale = Wiki dictionaries and encyclopedias (e.g. omegawiki, wiktionary, wikipedia, dbpedia) contain information (e.g. bilingual equivalences, morphological features, conjugations) that could be exploited to speed up the development of dictionaries for Apertium. This task aims at automatically building dictionaries by extracting different pieces of information from wiki structures such as interlingual links, infoboxes and/or from dbpedia RDF datasets.
| mentors = [[User:Firespeaker|Jonathan Washington]], [[User:Popcorndude]]
| more = /Dictionary induction from wikis
}}

{{IdeaSummary
| name = Dictionary induction from parallel corpora / Revive ReTraTos
| difficulty = Medium
| size = medium
| skills = C++, perl, python, xml, scripting, machine learning
| description = Extract dictionaries from parallel corpora
| rationale = Given a pair of monolingual modules and a parallel corpus, we should be able to run a program to align tagged sentences and give us the best entries that are missing from bidix. [[ReTraTos]] (from 2008) did this back in 2008, but it's from 2008. We want a program which builds and runs in 2022, and does all the steps for the user.
| mentors = [[User:Unhammer]], [[User:Popcorndude]]
| more = /Dictionary induction from parallel corpora
}}

{{IdeaSummary
| name = Extract morphological data from FLEx
| difficulty = hard
| size = large
| skills = python, XML parsing
| description = Write a program to extract data from [https://software.sil.org/fieldworks/ SIL FieldWorks] and convert as much as possible to monodix (and maybe bidix).
| rationale = There's a lot of potentially useful data in FieldWorks files that might be enough to build a whole monodix for some languages but it's currently really hard to use
| mentors = [[User:Popcorndude|Popcorndude]], [[User:TommiPirinen|Flammie]]
| more = /FieldWorks_data_extraction
}}

== Tooling ==

These are projects for people who would be comfortable digging through our C++ codebases (you will be doing a lot of that).

{{IdeaSummary
| name = Python API for Apertium
| difficulty = medium
| size = medium
| skills = C++, Python
| description = Update the Python API for Apertium to expose all Apertium modes and test with all major OSes
| rationale = The current Python API misses out on a lot of functionality, like phonemicisation, segmentation, and transliteration, and doesn't work for some OSes <s>like Debian</s>.
| mentors = [[User:Francis Tyers|Francis Tyers]]
| more = /Python API
}}

{{IdeaSummary
| name = Robust tokenisation in lttoolbox
| difficulty = Medium
| size = large
| skills = C++, XML, Python
| description = Improve the longest-match left-to-right tokenisation strategy in [[lttoolbox]] to handle spaceless orthographies.
| rationale = One of the most frustrating things about working with Apertium on texts "in the wild" is the way that the tokenisation works. If a letter is not specified in the alphabet, it is dealt with as whitespace, so e.g. you get unknown words split in two so you can end up with stuff like ^G$ö^k$ı^rmak$ which is terrible for further processing. Additionally, the system is nearly impossible to use for languages that don't use spaces, such as Japanese.
| mentors = [[User:Francis Tyers|Francis Tyers]], [[User:TommiPirinen|Flammie]]
| more = /Robust tokenisation
}}

{{IdeaSummary
| name = rule visualization tools
| difficulty = Medium
| size = either
| skills = python? javascript? XML
| description = make tools to help visualize the effect of various rules
| rationale = TODO see https://github.com/Jakespringer/dapertium for an example
| mentors = [[User:Firespeaker|Jonathan Washington]], [[User:Sevilay Bayatlı|Sevilay Bayatlı]], [[User:Popcorndude]]
| more = /Visualization tools
}}

{{IdeaSummary
| name = Extend Weighted transfer rules
| difficulty = Medium
| size = medium
| skills = C++, python
| description = The weighted transfer module is already applied to the chunker transfer rules. And the idea here is to extend that module to be applied to interchunk and postchunk transfer rules too.
| rationale = As a resource see https://github.com/aboelhamd/Weighted-transfer-rules-module
| mentors = [[User: Sevilay Bayatlı|Sevilay Bayatlı]]
| more = /Make a module
}}

{{IdeaSummary
| name = Automatic Error-Finder / Pseudo-Backpropagation
| difficulty = Hard
| size = large
| skills = python?
| description = Develop a tool to locate the approximate source of translation errors in the pipeline.
| rationale = Being able to generate a list of probable error sources automatically makes it possible to prioritize issues by frequency, frees up developer time, and is a first step towards automated generation of better rules.
| mentors = [[User:Popcorndude]]
| more = /Backpropagation
}}

{{IdeaSummary
| name = More Robust Recursive Transfer
| difficulty = Hard
| size = large
| skills = C++
| description = Ensure [[Apertium-recursive#Further_Documentation|Recursive Transfer]] survives ambiguous or incomplete parse trees
| rationale = Currently, one has to be very careful in writing recursive transfer rules to ensure they don't get too deep or ambiguous, and that they cover full sentences. See in particular issues [https://github.com/apertium/apertium-recursive/issues/97 97] and [https://github.com/apertium/apertium-recursive/issues/80 80]. We would like linguists to be able to fearlessly write recursive (rtx) rules based on what makes linguistic sense, and have rtx-proc/rtx-comp deal with the computational/performance side.
| mentors =
| more = /More_robust_recursive_transfer
}}

{{IdeaSummary
| name = CG-based Transfer
| difficulty = Hard
| size = large
| skills = C++
| description = Linguists already write dependency trees in [[Constraint Grammar]]. A following step could use these to reorder into target language trees.
| mentors =
| more =
}}

{{IdeaSummary
| name = Language Server Protocol
| difficulty = Medium
| size = medium
| skills = any programming language
| description = Build a [https://microsoft.github.io/language-server-protocol/|Language Server] for the various Apertium rule formats
| rationale = We have some static analysis tools and syntax highlighters already and it would be great if we could combine and expand them to support more text editors.
| mentors = [[User:Popcorndude]]
| more = /Language Server Protocol
}}

{{IdeaSummary
| name = WASM Compilation
| difficulty = hard
| size = medium
| skills = C++, Javascript
| description = Compile the pipeline modules to WASM and provide JS wrappers for them.
| rationale = There are situations where it would be nice to be able to run the entire pipeline in the browser
| mentors = [[User:Tino Didriksen|Tino Didriksen]]
| more = /WASM
}}

== Web ==

If you know Python and JavaScript, here's some ideas for improving our [https://apertium.org website]. Some of these should be fairly short and it would be a good idea to talk to the mentors about doing a couple of them together.

{{IdeaSummary
| name = Web API extensions
| difficulty = medium
| size = small
| skills = Python
| description = Update the web API for Apertium to expose all Apertium modes
| rationale = The current Web API misses out on a lot of functionality, like phonemicisation, segmentation, transliteration, and paradigm generation.
| mentors = [[User:Francis Tyers|Francis Tyers]], [[User:Firespeaker|Jonathan Washington]], [[User:Xavivars|Xavi Ivars]]
| more = /Apertium APY
}}

{{IdeaSummary
| name = Website Improvements: Misc
| difficulty = Medium
| size = small
| skills = html, css, js, python
| description = Improve elements of Apertium's web infrastructure
| rationale = Apertium's website infrastructure [[Apertium-html-tools]] and its supporting API [[APy|Apertium APy]] have numerous open issues. This project would entail choosing a subset of open issues and features that could realistically be completed in the summer. You're encouraged to speak with the Apertium community to see which features and issues are the most pressing.
| mentors = [[User:Firespeaker|Jonathan Washington]], [[User:Xavivars|Xavi Ivars]]
| more = /Website improvements
}}

{{IdeaSummary
| name = Website Improvements: Dictionary Lookup
| difficulty = Medium
| size = small
| skills = html, css, js, python
| description = Finish implementing dictionary lookup mode in Apertium's web infrastructure
| rationale = Apertium's website infrastructure [[Apertium-html-tools]] and its supporting API [[APy|Apertium APy]] have numerous open issues, including half-completed features like dictionary lookup. This project would entail completing the dictionary lookup feature. Some additional features which would be good to work would include automatic reverse lookups (so that a user has a better understanding of the results), grammatical information (such as the gender of nouns or the conjugation paradigms of verbs), and information about MWEs.
| mentors = [[User:Firespeaker|Jonathan Washington]], [[User:Xavivars|Xavi Ivars]], [[User:Popcorndude]]
| more = https://github.com/apertium/apertium-html-tools/issues/105 the open issue on GitHub
}}

{{IdeaSummary
| name = Website Improvements: Spell checking
| difficulty = Medium
| size = small
| skills = html, js, css, python
| description = Add a spell-checking interface to Apertium's web tools
| rationale = [[Apertium-html-tools]] has seen some prototypes for spell-checking interfaces (all in stale PRs and branches on GitHub), but none have ended up being quite ready to integrate into the tools. This project would entail polishing up or recreating an interface, and making sure [[APy]] has a mode that allows access to Apertium voikospell modules. The end result should be a slick, easy-to-use interface for proofing text, with intuitive underlining of text deemed to be misspelled and intuitive presentation and selection of alternatives. [https://github.com/apertium/apertium-html-tools/issues/390 the open issue on GitHub]
| mentors = [[User:Firespeaker|Jonathan Washington]], [[User:Xavivars|Xavi Ivars]]
| more = /Spell checker web interface
}}

{{IdeaSummary
| name = Website Improvements: Suggestions
| difficulty = Medium
| size = small
| skills = html, css, js, python
| description = Finish implementing a suggestions interface for Apertium's web infrastructure
| rationale = Some work has been done to add a "suggestions" interface to Apertium's website infrastructure [[Apertium-html-tools]] and its supporting API [[APy|Apertium APy]], whereby users can suggest corrected translations. This project would entail finishing that feature. There are some related [https://github.com/apertium/apertium-html-tools/issues/55 issues] and [https://github.com/apertium/apertium-html-tools/pull/252 PRs] on GitHub.
| mentors = [[User:Firespeaker|Jonathan Washington]], [[User:Xavivars|Xavi Ivars]]
| more = /Website improvements
}}

{{IdeaSummary
| name = Website Improvements: Orthography conversion interface
| difficulty = Medium
| size = small
| skills = html, js, css, python
| description = Add an orthography conversion interface to Apertium's web tools
| rationale = Several Apertium language modules (like Kazakh, Kyrgyz, Crimean Tatar, and Hñähñu) have orthography conversion modes in their mode definition files. This project would be to expose those modes through [[APy|Apertium APy]] and provide a simple interface in [[Apertium-html-tools]] to use them.
| mentors = [[User:Firespeaker|Jonathan Washington]], [[User:Xavivars|Xavi Ivars]]
| more = /Website improvements
}}

{{IdeaSummary
| name = Add support for NMT to web API
| difficulty = Medium
| size = medium
| skills = python, NMT
| description = Add support for a popular NMT engine to Apertium's web API
| rationale = Currently Apertium's web API [[APy|Apertium APy]], supports only Apertium language modules. But the front end could just as easily interface with an API that supports trained NMT models. The point of the project is to add support for one popular NMT package (e.g., translateLocally/Bergamot, OpenNMT or JoeyNMT) to the APy.
| mentors = [[User:Firespeaker|Jonathan Washington]], [[User:Xavivars|Xavi Ivars]]
| more =
}}

== Integrations ==

In addition to incorporating data from other projects, it would be nice if we could also make our data useful to them.

{{IdeaSummary
| name = OmniLingo and Apertium
| difficulty = medium
| size = either
| skills = JS, Python
| description = OmniLingo is a language learning system for practicing listening comprehension using Common Voice data. There is a lot of text processing involved (for example tokenisation) that could be aided by Apertium tools.
| rationale =
| mentors = [[User:Francis Tyers|Francis Tyers]]
| more = /OmniLingo
}}

{{IdeaSummary
| name = Support for Enhanced Dependencies in UD Annotatrix
| difficulty = medium
| size = medium
| skills = NodeJS
| description = UD Annotatrix is an annotation interface for Universal Dependencies, but does not yet support all functionality.
| rationale =
| mentors = [[User:Francis Tyers|Francis Tyers]]
| more = /Annotatrix enhanced dependencies
}}

<!--
This one was done, but could do with more work. Not sure if it's a full gsoc though?

{{IdeaSummary
| name = User-friendly lexical selection training
| difficulty = Medium
| skills = Python, C++, shell scripting
| description = Make it so that training/inference of lexical selection rules is a more user-friendly process
| rationale = Our lexical selection module allows for inferring rules from corpora and word alignments, but the procedure is currently a bit messy, with various scripts involved that require lots of manual tweaking, and many third party tools to be installed. The goal of this task is to make the procedure as user-friendly as possible, so that ideally only a simple config file would be needed, and a driver script would take care of the rest.
| mentors = [[User:Unhammer|Unhammer]], [[User:Mlforcada|Mikel Forcada]]
| more = /User-friendly lexical selection training
}}
-->


{{IdeaSummary
; Transfer rule learning
| name = UD and Apertium integration
* Sánchez-Martínez, F. and Forcada, M.L. (2009) "[http://www.dlsi.ua.es/~fsanchez/pub/pdf/sanchez-martinez09b.pdf Inferring shallow-transfer machine translation rules from small parallel corpora]" In Journal of Artificial Intelligence Research. volume 34, p. 605-635.
| difficulty = Entry level
| size = medium
| skills = python, javascript, HTML, (C++)
| description = Create a range of tools for making Apertium compatible with Universal Dependencies
| rationale = Universal dependencies is a fast growing project aimed at creating a unified annotation scheme for treebanks. This includes both part-of-speech and morphological features. Their annotated corpora could be extremely useful for Apertium for training models for translation. In addition, Apertium's rule-based morphological descriptions could be useful for software that relies on Universal dependencies.
| mentors = [[User:Francis Tyers]], [[User:Firespeaker| Jonathan Washington]], [[User:Popcorndude]]
| more = /UD and Apertium integration
}}


; Target-language driven part-of-speech tagger training
* Sánchez-Martínez, F.; Pérez-Ortiz, J.A. and Forcada, M.L. (2008) "[http://www.springerlink.com/content/m452802q3536044v/fulltext.pdf Using target-language information to train part-of-speech taggers for machine translation]". In Machine Translation, volume 22, numbers 1-2, p. 29-66.
[[Category:Development]]
[[Category:Development]]
[[Category:Google Summer of Code]]

Latest revision as of 09:15, 4 March 2024

This is the ideas page for Google Summer of Code, here you can find ideas on interesting projects that would make Apertium more useful for people and improve or expand our functionality.

Current Apertium contributors: If you have an idea please add it below, if you think you could mentor someone in a particular area, add your name to "Interested mentors" using ~~~.

Prospective GSoC contributors: The page is intended as an overview of the kind of projects we have in mind. If one of them particularly piques your interest, please come and discuss with us on #apertium on irc.oftc.net (more on IRC), mail the mailing list, or draw attention to yourself in some other way.

Note that if you have an idea that isn't mentioned here, we would be very interested to hear about it.

Here are some more things you could look at:


If you're a prospective GSoC contributor trying to propose a topic, the recommended way is to request a wiki account and then go to 

http://wiki.apertium.org/wiki/User:[[your username]]/GSoC2023Proposal

and click the "create" button near the top of the page. It's also nice to include [[Category:GSoC_2023_student_proposals]] to help organize submitted proposals.

Language Data[edit]

Can you read or write a language other than English (and we do mean any language)? If so, you can help with one of these and we can help you figure out the technical parts.


Develop a morphological analyser[edit]

  • Difficulty:
    3. Entry level
  • Size: Multiple lengths possible (discuss with the mentors which option is better for you)
  • Required skills:
    XML or HFST or lexd
  • Description:
    Write a morphological analyser and generator for a language that does not yet have one
  • Rationale:
    A key part of an Apertium machine translation system is a morphological analyser and generator. The objective of this task is to create an analyser for a language that does not yet have one.
  • Mentors:
    Francis Tyers, Jonathan Washington, Sevilay Bayatlı, Hossep, nlhowell, User:Popcorndude
  • read more...


apertium-separable language-pair integration[edit]

  • Difficulty:
    2. Medium
  • Size: Small
  • Required skills:
    XML, a scripting language (Python, Perl), some knowledge of linguistics and/or at least one relevant natural language
  • Description:
    Choose a language you can identify as having a good number of "multiwords" in the lexicon. Modify all language pairs in Apertium to use the Apertium-separable module to process the multiwords, and clean up the dictionaries accordingly.
  • Rationale:
    Apertium-separable is a newish module to process lexical items with discontinguous dependencies, an area where Apertium has traditionally fallen short. Despite all the module has to offer, many translation pairs still don't use it.
  • Mentors:
    Jonathan Washington, User:Popcorndude
  • read more...


Bring an unreleased translation pair to releasable quality[edit]

  • Difficulty:
    2. Medium
  • Size: Large
  • Required skills:
    shell scripting
  • Description:
    Take an unstable language pair and improve its quality, focusing on testvoc
  • Rationale:
    Many Apertium language pairs have large dictionaries and have otherwise seen much development, but are not of releasable quality. The point of this project would be bring one translation pair to releasable quality. This would entail obtaining good naïve coverage and a clean testvoc.
  • Mentors:
    Jonathan Washington, Sevilay Bayatlı, User:Unhammer, Hèctor Alòs i Font
  • read more...


Develop a prototype MT system for a strategic language pair[edit]

  • Difficulty:
    2. Medium
  • Size: Large
  • Required skills:
    XML, some knowledge of linguistics and of one relevant natural language
  • Description:
    Create a translation pair based on two existing language modules, focusing on the dictionary and structural transfer
  • Rationale:
    Choose a strategic set of languages to develop an MT system for, such that you know the target language well and morphological transducers for each language are part of Apertium. Develop an Apertium MT system by focusing on writing a bilingual dictionary and structural transfer rules. Expanding the transducers and disambiguation, and writing lexical selection rules and multiword sequences may also be part of the work. The pair may be an existing prototype, but if it's a heavily developed but unreleased pair, consider applying for "Bring an unreleased translation pair to releasable quality" instead.
  • Mentors:
    Jonathan Washington, Sevilay Bayatlı, User:Unhammer, Hèctor Alòs i Font
  • read more...


Add a new variety to an existing language[edit]

  • Difficulty:
    3. Entry level
  • Size: Multiple lengths possible (discuss with the mentors which option is better for you)
  • Required skills:
    XML, some knowledge of linguistics and of one relevant natural language
  • Description:
    Add a language variety to one or more released pairs, focusing on the dictionary and lexical selection
  • Rationale:
    Take a released language, and define a new language variety for it: e.g. Quebec French or Provençal Occitan. Then add the new variety to one or more released language pairs, without diminishing the quality of the pre-existing variety(ies). The objective is to facilitate the generation of varieties for languages with a weak standardisation and/or pluricentric languages.
  • Mentors:
    Hèctor Alòs i Font, Jonathan Washington,Sevilaybayatlı
  • read more...


Leverage and integrate language preferences into language pairs[edit]

  • Difficulty:
    3. Entry level
  • Size: Medium
  • Required skills:
    XML, some knowledge of linguistics and of one relevant natural language
  • Description:
    Update language pairs with lexical and orthographical variations to leverage the new preferences functionality
  • Rationale:
    Currently, preferences are implemented via language variant, which relies on multiple dictionaries, increasing compilation time exponentially every time a new preference gets introduced.
  • Mentors:
    Xavi Ivars User:Unhammer
  • read more...


Add Capitalization Handling Module to a Language Pair[edit]

  • Difficulty:
    3. Entry level
  • Size: Small
  • Required skills:
    XML, knowledge of some relevant natural language
  • Description:
    Update a language pair to make use make use of the new Capitalization handling module
  • Rationale:
    Correcting capitalization via transfer rules is tedious and error prone, but putting them in a separate set of rules should allow them to be handled in a more concise and maintainable way. Additionally, it is possible that capitalization rule could be moved to monolingual modules, thus reducing development effort on translators.
  • Mentors:
    User:Popcorndude
  • read more...

Data Extraction[edit]

A lot of the language data we need to make our analyzers and translators work already exists in other forms and we just need to figure out how to convert it. If you know of another source of data that isn't listed, we'd love to hear about it.


dictionary induction from wikis[edit]

  • Difficulty:
    2. Medium
  • Size: Multiple lengths possible (discuss with the mentors which option is better for you)
  • Required skills:
    MySQL, mediawiki syntax, perl, maybe C++ or Java; Java, Scala, RDF, and DBpedia to use DBpedia extraction
  • Description:
    Extract dictionaries from linguistic wikis
  • Rationale:
    Wiki dictionaries and encyclopedias (e.g. omegawiki, wiktionary, wikipedia, dbpedia) contain information (e.g. bilingual equivalences, morphological features, conjugations) that could be exploited to speed up the development of dictionaries for Apertium. This task aims at automatically building dictionaries by extracting different pieces of information from wiki structures such as interlingual links, infoboxes and/or from dbpedia RDF datasets.
  • Mentors:
    Jonathan Washington, User:Popcorndude
  • read more...


Dictionary induction from parallel corpora / Revive ReTraTos[edit]

  • Difficulty:
    2. Medium
  • Size: Medium
  • Required skills:
    C++, perl, python, xml, scripting, machine learning
  • Description:
    Extract dictionaries from parallel corpora
  • Rationale:
    Given a pair of monolingual modules and a parallel corpus, we should be able to run a program to align tagged sentences and give us the best entries that are missing from bidix. ReTraTos (from 2008) did this back in 2008, but it's from 2008. We want a program which builds and runs in 2022, and does all the steps for the user.
  • Mentors:
    User:Unhammer, User:Popcorndude
  • read more...


Extract morphological data from FLEx[edit]

  • Difficulty:
    1. Hard
  • Size: Large
  • Required skills:
    python, XML parsing
  • Description:
    Write a program to extract data from SIL FieldWorks and convert as much as possible to monodix (and maybe bidix).
  • Rationale:
    There's a lot of potentially useful data in FieldWorks files that might be enough to build a whole monodix for some languages but it's currently really hard to use
  • Mentors:
    Popcorndude, Flammie
  • read more...

Tooling[edit]

These are projects for people who would be comfortable digging through our C++ codebases (you will be doing a lot of that).


Python API for Apertium[edit]

  • Difficulty:
    2. Medium
  • Size: Medium
  • Required skills:
    C++, Python
  • Description:
    Update the Python API for Apertium to expose all Apertium modes and test with all major OSes
  • Rationale:
    The current Python API misses out on a lot of functionality, like phonemicisation, segmentation, and transliteration, and doesn't work for some OSes like Debian.
  • Mentors:
    Francis Tyers
  • read more...


Robust tokenisation in lttoolbox[edit]

  • Difficulty:
    2. Medium
  • Size: Large
  • Required skills:
    C++, XML, Python
  • Description:
    Improve the longest-match left-to-right tokenisation strategy in lttoolbox to handle spaceless orthographies.
  • Rationale:
    One of the most frustrating things about working with Apertium on texts "in the wild" is the way that the tokenisation works. If a letter is not specified in the alphabet, it is dealt with as whitespace, so e.g. you get unknown words split in two so you can end up with stuff like ^G$ö^k$ı^rmak$ which is terrible for further processing. Additionally, the system is nearly impossible to use for languages that don't use spaces, such as Japanese.
  • Mentors:
    Francis Tyers, Flammie
  • read more...


rule visualization tools[edit]


Extend Weighted transfer rules[edit]


Automatic Error-Finder / Pseudo-Backpropagation[edit]

  • Difficulty:
    1. Hard
  • Size: Large
  • Required skills:
    python?
  • Description:
    Develop a tool to locate the approximate source of translation errors in the pipeline.
  • Rationale:
    Being able to generate a list of probable error sources automatically makes it possible to prioritize issues by frequency, frees up developer time, and is a first step towards automated generation of better rules.
  • Mentors:
    User:Popcorndude
  • read more...


More Robust Recursive Transfer[edit]

  • Difficulty:
    1. Hard
  • Size: Large
  • Required skills:
    C++
  • Description:
    Ensure Recursive Transfer survives ambiguous or incomplete parse trees
  • Rationale:
    Currently, one has to be very careful in writing recursive transfer rules to ensure they don't get too deep or ambiguous, and that they cover full sentences. See in particular issues 97 and 80. We would like linguists to be able to fearlessly write recursive (rtx) rules based on what makes linguistic sense, and have rtx-proc/rtx-comp deal with the computational/performance side.
  • Mentors:
  • read more...


CG-based Transfer[edit]

  • Difficulty:
    1. Hard
  • Size: Large
  • Required skills:
    C++
  • Description:
    Linguists already write dependency trees in Constraint Grammar. A following step could use these to reorder into target language trees.
  • Rationale:
    {{{rationale}}}
  • Mentors:
  • [[|read more...]]


Language Server Protocol[edit]


WASM Compilation[edit]

  • Difficulty:
    1. Hard
  • Size: Medium
  • Required skills:
    C++, Javascript
  • Description:
    Compile the pipeline modules to WASM and provide JS wrappers for them.
  • Rationale:
    There are situations where it would be nice to be able to run the entire pipeline in the browser
  • Mentors:
    Tino Didriksen
  • read more...

Web[edit]

If you know Python and JavaScript, here's some ideas for improving our website. Some of these should be fairly short and it would be a good idea to talk to the mentors about doing a couple of them together.


Web API extensions[edit]

  • Difficulty:
    2. Medium
  • Size: Small
  • Required skills:
    Python
  • Description:
    Update the web API for Apertium to expose all Apertium modes
  • Rationale:
    The current Web API misses out on a lot of functionality, like phonemicisation, segmentation, transliteration, and paradigm generation.
  • Mentors:
    Francis Tyers, Jonathan Washington, Xavi Ivars
  • read more...


Website Improvements: Misc[edit]

  • Difficulty:
    2. Medium
  • Size: Small
  • Required skills:
    html, css, js, python
  • Description:
    Improve elements of Apertium's web infrastructure
  • Rationale:
    Apertium's website infrastructure Apertium-html-tools and its supporting API Apertium APy have numerous open issues. This project would entail choosing a subset of open issues and features that could realistically be completed in the summer. You're encouraged to speak with the Apertium community to see which features and issues are the most pressing.
  • Mentors:
    Jonathan Washington, Xavi Ivars
  • read more...


Website Improvements: Dictionary Lookup[edit]

  • Difficulty:
    2. Medium
  • Size: Small
  • Required skills:
    html, css, js, python
  • Description:
    Finish implementing dictionary lookup mode in Apertium's web infrastructure
  • Rationale:
    Apertium's website infrastructure Apertium-html-tools and its supporting API Apertium APy have numerous open issues, including half-completed features like dictionary lookup. This project would entail completing the dictionary lookup feature. Some additional features which would be good to work would include automatic reverse lookups (so that a user has a better understanding of the results), grammatical information (such as the gender of nouns or the conjugation paradigms of verbs), and information about MWEs.
  • Mentors:
    Jonathan Washington, Xavi Ivars, User:Popcorndude
  • [the open issue on GitHub|read more...]


Website Improvements: Spell checking[edit]

  • Difficulty:
    2. Medium
  • Size: Small
  • Required skills:
    html, js, css, python
  • Description:
    Add a spell-checking interface to Apertium's web tools
  • Rationale:
    Apertium-html-tools has seen some prototypes for spell-checking interfaces (all in stale PRs and branches on GitHub), but none have ended up being quite ready to integrate into the tools. This project would entail polishing up or recreating an interface, and making sure APy has a mode that allows access to Apertium voikospell modules. The end result should be a slick, easy-to-use interface for proofing text, with intuitive underlining of text deemed to be misspelled and intuitive presentation and selection of alternatives. the open issue on GitHub
  • Mentors:
    Jonathan Washington, Xavi Ivars
  • read more...


Website Improvements: Suggestions[edit]

  • Difficulty:
    2. Medium
  • Size: Small
  • Required skills:
    html, css, js, python
  • Description:
    Finish implementing a suggestions interface for Apertium's web infrastructure
  • Rationale:
    Some work has been done to add a "suggestions" interface to Apertium's website infrastructure Apertium-html-tools and its supporting API Apertium APy, whereby users can suggest corrected translations. This project would entail finishing that feature. There are some related issues and PRs on GitHub.
  • Mentors:
    Jonathan Washington, Xavi Ivars
  • read more...


Website Improvements: Orthography conversion interface[edit]

  • Difficulty:
    2. Medium
  • Size: Small
  • Required skills:
    html, js, css, python
  • Description:
    Add an orthography conversion interface to Apertium's web tools
  • Rationale:
    Several Apertium language modules (like Kazakh, Kyrgyz, Crimean Tatar, and Hñähñu) have orthography conversion modes in their mode definition files. This project would be to expose those modes through Apertium APy and provide a simple interface in Apertium-html-tools to use them.
  • Mentors:
    Jonathan Washington, Xavi Ivars
  • read more...


Add support for NMT to web API[edit]

  • Difficulty:
    2. Medium
  • Size: Medium
  • Required skills:
    python, NMT
  • Description:
    Add support for a popular NMT engine to Apertium's web API
  • Rationale:
    Currently Apertium's web API Apertium APy, supports only Apertium language modules. But the front end could just as easily interface with an API that supports trained NMT models. The point of the project is to add support for one popular NMT package (e.g., translateLocally/Bergamot, OpenNMT or JoeyNMT) to the APy.
  • Mentors:
    Jonathan Washington, Xavi Ivars
  • [[|read more...]]

Integrations[edit]

In addition to incorporating data from other projects, it would be nice if we could also make our data useful to them.


OmniLingo and Apertium[edit]

  • Difficulty:
    2. Medium
  • Size: Multiple lengths possible (discuss with the mentors which option is better for you)
  • Required skills:
    JS, Python
  • Description:
    OmniLingo is a language learning system for practicing listening comprehension using Common Voice data. There is a lot of text processing involved (for example tokenisation) that could be aided by Apertium tools.
  • Rationale:
  • Mentors:
    Francis Tyers
  • read more...


Support for Enhanced Dependencies in UD Annotatrix[edit]

  • Difficulty:
    2. Medium
  • Size: Medium
  • Required skills:
    NodeJS
  • Description:
    UD Annotatrix is an annotation interface for Universal Dependencies, but does not yet support all functionality.
  • Rationale:
  • Mentors:
    Francis Tyers
  • read more...


UD and Apertium integration[edit]

  • Difficulty:
    3. Entry level
  • Size: Medium
  • Required skills:
    python, javascript, HTML, (C++)
  • Description:
    Create a range of tools for making Apertium compatible with Universal Dependencies
  • Rationale:
    Universal dependencies is a fast growing project aimed at creating a unified annotation scheme for treebanks. This includes both part-of-speech and morphological features. Their annotated corpora could be extremely useful for Apertium for training models for translation. In addition, Apertium's rule-based morphological descriptions could be useful for software that relies on Universal dependencies.
  • Mentors:
    User:Francis Tyers, Jonathan Washington, User:Popcorndude
  • read more...
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