Ideas for Google Summer of Code

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 — or just have interests or ideas for that, add your name to "Interested parties" using ~~~

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.freenode.net, mail the mailing list, or draw attention to yourself in some other way.

Maybe take a look at some open bugs ?

Difficulty = 1 (Very Hard) ... 4 (Entry level)

See the list sorted by: difficulty level, theme.

Task	Difficulty	Description	Rationale	Requirements	Interested parties
Improve interoperability	3. Medium	Either to modify Apertium to accept different formats, or to modify the other tools to accept the Apertium format, or alternatively write some kind of generic "glue" code that converts between them.	There is a lot of great free software that could be used with the Apertium engine. We already have support for SFST (for morphological analysis) and Constraint Grammar (CG, for disambiguation) and use CG in several language pairs. It would be cool to have support for other tools, such as being able to use grammars from Freeling or link grammar to do preprocessing. Unfortunately these, along with many other tools have incompatible input/output formats.	C, C++, XML	Francis Tyers, Jimregan
Accent and diacritic restoration	3. 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	Francis Tyers
Handling texts without accents or diacritics	3. Medium	Modify the linguistic data in an Apertium language-pair package so that it can accept text without accents or diacritics (or partially diacriticised). The task may constitute an alternative solution to the problem in the previous task.	see: Accent and diacritic restoration	Perl or Python, familiarity with linguistic issues.	Mlforcada, Jimregan
Porting	3. Medium	Port Apertium to Windows and (Mac OS/X - hecho. 17:32, 4 November 2008) complete with nice installers and all that jazz. Apertium currently compiles on Windows (see Apertium on Windows), but we'd like to see it compile with a free tool-chain (MingGW, etc.)	While we all might use GNU/Linux, there are a lot of people out there who don't, some of them use Microsoft's Windows, others use Mac OS. It would be nice for these people to be able use Apertium too.	C++, autotools, experience in programming on Windows.	Francis Tyers, Jimregan, Xavi Ivars
Lexical selection	1. Very Hard	Write a prototype lexical selection module for Apertium using a combination of rule-based and statistical approaches, or maybe only an statistical approach.	Lexical selection is the task of choosing a sense (meaning) for a word out of a number of possible senses (related to word sense disambiguation), when languages are close, they often share semantic ambiguity, when they are further apart they do not, so for example Spanish "estación" can be either "station", "season" or "resort" in English. Lexical selection is the task of choosing the right one. See also: Category:Lexical selection	C++, XML, good knowledge of statistics.	Jimregan, Fsanchez
Interfaces	4. Entry level	Create plugins or extensions for popular free software applications to include support for translation using Apertium. We'd expect at least Firefox and Evolution (or Thunderbird), but to start with something more easy we have half-finished plugins for Pidgin and XChat that could use some love. The more the better!	Apertium currently runs as a stand alone translator. It would be great if it was integrated in other free software applications. For example so instead of copy/pasting text out of your email, you could just click a button and have it translated in place.	Depends on the application chosen, but probably C, C++, Python or Perl.	Francis Tyers, Jimregan
Linguistically-driven filtering of the bilingual phrases used to infer shallow-transfer rules	3. 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. This may also involve porting it to use Unicode.	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.	Fsanchez
Use of context-dependent lexicalized categories in the inference of shallow-transfer rules	2. Hard	Re-working apertium-transfer-training-tools to use context-dependent lexicalized categories in the inference of shallow-transfer rules. This may also involve porting it to use Unicode.	Apertium-transfer-training-tools generates shallow-transfer rules from aligned parallel corpora. It uses an small set of lexicalized categories, categories that are usually involved in lexical changes, such as prepositions, pronouns or auxiliary verbs. Lexicalized 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.	Fsanchez
Automated lexical extraction	2. Hard	Writing a C++ wrapper around Markus Forsberg's Extract tool (version 2.0) as a library to allow it to be used with Apertium paradigms and TSX files as input into its paradigms and constraints.	One of the things that takes a lot of time when creating a new language pair is constructing the monodices. The extract tool can greatly reduce the time this takes by matching lemmas to paradigms based on distribution in a corpus.	Haskell, C++, XML	Francis Tyers
Generating grammar checkers	3. Medium	The data that come with Apertium (morphological analysers) could be used to create grammar checkers. This task would be to work on an automatic converter for Apertium formats (dictionaries, disambiguation rules) to other popular grammar checker formats, or alternatively work on a standalone grammar checker. Maybe using something like languagetool or An Gramadóir	Grammar 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, whatever programming language and natural language are used for testing.	Francis Tyers, Jimregan, Marcin Miłkowski
Support for agglutinative languages	2. Hard	Propose a new dictionary format that is suited to languages with agglutinative morphology and modify the morphological compiler/analyser.	Our dictionary format isn't particularly suited to agglutinative languages, and those with complex morphologies. There are many of these types of languages in the world, so it would be good to support them better. See also: Agglutination	C++, XML, knowledge of a language with these features (e.g. Finnish, Basque, Turkish, Estonian, Aymara, etc.)	Sortiz
Complex multiwords	2. 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 adj nom because the adjective has a lot of inflection.	C, C++, XML	Francis Tyers, Jimregan
Adopt a language pair	4. Entry 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 — which are specified in a declarative language)	Apertium has a few pairs of languages (e.g. sv-da, 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.	XML, a scripting language (Python, Perl), good knowledge of the language pair adopted.	Francis Tyers, Jimregan
Word compounder and de-compounder	4. Entry level	Write a de-compounder and compounder for Apertium.	Many languages in the world have compound words, in Europe e.g. German, Dutch, Danish, etc. These are often very low frequency or completely novel, and as such do not exist in our dictionaries. If we had some software to split these into their constituent parts we might be able to translate them, and improve accuracy on our pairs with these languages. See also bug #13, and the page Compounds	C, C++, XML	Francis Tyers
Post-edition tool	3. 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 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.	XML, PHP, Python, C, C++, whichever programming language.	Sortiz, Jimregan, Marcin Miłkowski
Lexical insertion tool	3. Medium	Improving the current web based dictionary application to insert new word pairs into the Apertium dictionaries. This would involve both improving the functionality, and efficiency of the software.	Currently people have to edit XML in order to add words to the dictionaries. We have a web application, written in Python that does a lot of this work, but it still lacks some functionality, for example multiwords, and complete support for the new dictionary format. What is more it is quite slow and memory intensive.	Python	Francis Tyers
Generating spell checkers	4. Entry level	The data that come with Apertium (morphological analysers) could be used to create spell checkers. This task would be to work on an automatic converter for Apertium formats to other popular spell checker formats. Maybe using something ispell, myspell, hunspell, youspell, etc.	Spell checkers can be useful especially before translating. They are one of the basic 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). This will be particulary useful for minority languages having an Apertium translator but not having a free spell checker, and also to use spell checking tools as a controlled language tool.	XML, whatever programming language and natural language are used for testing.	Sortiz
Detect 'hidden' unknown words	3. 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.	Sortiz, Fsanchez
Format filters	4. Entry level	Making apertium capable of dealing with more different formats, for the minimum: files marked up with LaTeX and Wiki.	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.	Mlforcada Francis Tyers, Jimregan
Part of speech detection for unknown words	3. Medium	Allow unknown words to be processed by transfer rules	At the moment, unknown words are ignored by transfer rules; however, the part-of-speech tagger could be modified to add likely tags for unknown words, which could then be used in transfer, which would improve sentence level translation. In addition, certain factors of the morphology of the unknown word could be taken into account (e.g., the suffix '-ing' in an unknown English word implies a verb) to increase the 'confidence' in an analysis.	C++ preferable	Jimregan
Multi-engine translation synthesiser	3. Medium	Write synthesiser to make a "better" translation out of several translations.	There are other open-source machine translation systems in existence (for example Moses and OpenLogos), the point of this project would be to write a "synthesiser" which can, given several translations, produce a better translation. The program will probably take each of the output sentences from each system, decompose them into chunks or phrases and then score them against a language model to come to the final synthesised translation. Care should be taken to not overly bias fluent translations over adequate translations.	C++ or Python (for prototyping)	Francis Tyers
Trigram tagger	3. Medium	Modify the tagger to use trigrams instead of bigrams	We use bigrams -- for speed -- in the tagger, but now computers have improved and we have 3-stage transfer which will dominate CPU usage anyway. See also these questions	C++.	Jacob Nordfalk
Language independent target-language tagger training	2. Hard	Modify apertium-tagger-training-tools so that it does not need the segmentation provided by the transfer rules in order to score translations, and to prune the k-best list of possible translations at run-time for efficiency	apertium-tagger-training-tools is a program for doing target language tagger training. This means that it tunes the parameters of an HMM model based on the quality of the translations through the whole system. At the moment this relies on the segmentation of the input by the transfer rules, and also runs all the possible translations (undisambiguated). It would be good to be able to run it without having this segmentation.	C++	Fsanchez Francis Tyers Mlforcada
Daemon mode	3. Medium	Write a program to allow Apertium to be run in "server" or "daemon" mode.	When a lot of documents are translated, we launch the translator (the whole pipeline) multiple times, this is results in it being slower than ideal because of the time taken in process creation, loading transducers, grammars etc. and OS overheads. If it were to be run as a server or daemon, then these operations would only need to be performed once.	C++	Xerakko
Geriaoueg vocabulary assistant	4. Entry 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	Francis Tyers Donnek

Further reading

Accent and diacritic restoration

• Simard, Michel (1998). "Automatic Insertion of Accents in French Texts". Proceedings of EMNLP-3. Granada, Spain.
• Rada F. Mihalcea. (2002). "Diacritics Restoration: Learning from Letters versus Learning from Words". Lecture Notes in Computer Science 2276/2002 pp. 96--113
• G. De Pauw, P. W. Wagacha; G.M. de Schryver (2007) "Automatic diacritic restoration for resource-scarce languages". Proceedings of Text, Speech and Dialogue, Tenth International Conference. pp. 170--179
• P.W. Wagacha; G. De Pauw; P.W. Githinji (2006) "A grapheme-based approach to accent restoration in Gĩkũyũ". Proceedings of the Fifth International Conference on Language Resources and Evaluation
• D. Yarowsky (1994) "A Comparison Of Corpus-Based Techniques For Restoring Accents In Spanish And French Text". Proceedings, 2nd annual workshop on very large corpora. pp. 19--32

Lexical selection

• Ide, N. and Véronis, J. (1998) "Word Sense Disambiguation: The State of the Art". Computational Linguistics 24(1)

Automated lexical extraction

• M. Forsberg H. Hammarström A. Ranta. "Morphological Lexicon Extraction from Raw Text Data". FinTAL 2006, LNAI 4139, pp. 488--499.

Support for agglutinative languages

• Beesley, K. R and Karttunen, L. (2000) "Finite-State Non-Concatenative Morphotactics". SIGPHON-2000, Proceedings of the Fifth Workshop of the ACLSpecial Interest Group in Computational Phonology, pp. 1--12,

Transfer rule learning

• Sánchez-Martínez, F. and Forcada, M.L. (2007) "Automatic induction of shallow-transfer rules for open-source machine translation", in Proceedings of TMI 2007, pp.181-190 (paper, poster)

Compounding and de-compounding

• Koehn, P. and Knight, K. (2003) "Empirical Methods for Compound Splitting". 11th Conference of the European Chapter of the Association for Computational Linguistics, (EACL2003).
• Brown, R. (2002) "Corpus-Driven Splitting of Compound Words". TMI 2002
• Moa, H. (2005) "Compounds and other oddities in machine translation". Proceedings of the 15th NODALIDA conference, Joensuu 2005.

Multi-engine machine translation

• Sergei Nirenburg and Robert Frederking (1994) "Toward Multi-Engine Machine Translation". Proceedings of the workshop on Human Language Technology. pp. 147 - 151
• Shyamsundar Jayaraman and Alon Lavie (2005) "Multi-Engine Machine Translation Guided by Explicit Word Matching". ACL 2005