Automatic lexicon extraction from comparable, non-parallel corpora
An automated approach of extracting bilingual lexicon (or dictionary) from comparable, non-parallel corpora is developed, implemented and tested. The corpora used are of bilingual domains containing 381,553 English and 92,610 Tagalog terms, with corresponding 4,817 and 3,421 distinct root words, res...
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| Format: | text |
| Language: | English |
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Animo Repository
2004
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| Online Access: | https://animorepository.dlsu.edu.ph/etd_masteral/3173 |
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| Institution: | De La Salle University |
| Language: | English |
| Summary: | An automated approach of extracting bilingual lexicon (or dictionary) from comparable, non-parallel corpora is developed, implemented and tested. The corpora used are of bilingual domains containing 381,553 English and 92,610 Tagalog terms, with corresponding 4,817 and 3,421 distinct root words, respectively. The terms in the resulting lexicon are grouped into their respective senses. For the 100 test words (50 high frequency words, HFW and 50 low frequency words, LFW), 50.29% (HFW) and 31.37% (LFW) of the expected translations in all clusters were generated (called recall test). 56.12% (HFW) and 21.98% (LFW) of the expected translations within clusters were generated (called precision test). The overall results represented by the F-measure (a combination of recall and precision), show that 10.65% of the expected translations for the 100 test words were generated. Inclusion of several natural language resources (e.g. lexicon expansion to include alternate senses, word per word lexicon translation, larger comparable corpora), improvement of preprocessing techniques (e.g. stemming and part of speech tagging for Tagalog), and other enhancements (e.g. smoothing of sparse data and disambiguation techniques) would improve the overall performance of the system. |
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