User:Francis Tyers/An MT system in one thousand steps
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The idea of this page is to split the creation of a new language pair into bite-sized chunks that could be done in around two-hours or less by an experienced developer. One use of the page might be to organise work into tasks for the Google Code-in or to parallelise development between multiple people.
Research
- Amass resources (1 task)
- Find a grammar of language X and of language Y
- Find a bilingual dictionary X-Y
- Find bilingual dictionaries X-Z and Y-Z
- Find 1-3 large monolingual corpora of language X and language Y
- Find a parallel corpus of language X and language Y
Morphological analysers (~200 tasks)
For languages X and Y:
- Add closed categories
- Add adpositions and conjunctions (1 task)
- Add determiners (1 task)
- Add pronouns (1 task)
- Add numerals (1 task)
- At least 1-100 leaving out compositional numerals
- Categorise and lemmatise words by frequency
- Create frequency lists from your corpora
- Categorise words (15 tasks)
- Lemmatise words (15 tasks)
- Add open categories by frequency
- Add nouns (26 tasks)
- Add proper nouns (16 tasks)
- Add adjectives (15 tasks)
- Add adverbs (3 tasks)
- Add verbs (20 tasks)
For adding the open categories, we assume around 100 words per task.
Bilingual dictionary
- Add closed categories (1 task)
- Morphologically analyse and word align parallel corpus
- Extract bilingual dictionary candidates
- Proofread and add open category candidates by frequency
- Take freely available dictionaries online
- Convert to lttoolbox format
- Add and check nouns (2 tasks)
- Add and check verbs (2 tasks)
- Add and check adjectives (2 tasks)
- Add and check adverbs (2 tasks)
- Convert to lttoolbox format
- Add entries by frequency
- Add nouns (10 tasks)
- Add verbs (10 tasks)
- Add adjectives (10 tasks)
- Add adverbs (10 tasks)
Disambiguation
- Make a list of most frequent ambiguities (both lemma ambiguities and POS ambiguities) (1 task)
- Write disambiguation rules for most frequent POS+lemma ambiguities (15 tasks)
- Write disambiguation rules for most frequent POS ambiguities (15 tasks)
- Train statistical POS tagger (1 task)
- Find bad POS disambiguation leading to bad translation (15 tasks)
- Write rules to fix bad POS disambiguation (15 tasks)
Lexical selection
- POS tag and word align parallel corpus (1 task)
- Extract default translation rules (1 task)
- Extract context rules (maximum entropy) (1 task)
- Make a list of most frequent ambiguities (both lemma ambiguities and POS ambiguities) (1 task)
- Write lexical selection rules for frequent ambiguities (10 tasks)
Transfer rules
- Write a contrastive grammar
Evaluation
- Translate 500 words of text, postedit and calculate WER (4 tasks)