Abstract
Bilingual lexicon is a useful language resource, but such data rarely available for lower-density language pairs, especially for those that are closely related. The lack or absence of parallel and comparable corpora makes bilingual lexicon extraction becomes a difficult task. Using a third language to link two other languages is a well-known solution in low-resource situation, which usually requires only two input bilingual lexicons to automatically induce the new one. This approach, however, is weak in measuring semantic distance between bilingual word pairs because it has never been demonstrated to utilize the complete structures of the input bilingual lexicons as dropped meanings negatively influence the result. This research discuss a constraint approach to pivot-based lexicon induction in case the target language pair are closely related. We create constraints from language similarity and model the structures of the input dictionaries as an optimization problem whose solution produces optimally correct target bilingual lexicon. In addition, we enable created bilingual lexicons of low-resource languages accessible through service grid federation.
| Original language | English |
|---|---|
| Title of host publication | Cognitive Technologies |
| Publisher | Springer-Verlag |
| Pages | 109-123 |
| Number of pages | 15 |
| Edition | 9789811077920 |
| DOIs | |
| Publication status | Published - 2018 Jan 1 |
| Externally published | Yes |
Publication series
| Name | Cognitive Technologies |
|---|---|
| Number | 9789811077920 |
| ISSN (Print) | 1611-2482 |
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Keywords
- Bilingual dictionary induction
- Constraint satisfaction problem
- Low-resource languages
- Pivot language
- Weighted partial max-SAT
ASJC Scopus subject areas
- Software
- Artificial Intelligence
Cite this
A constraint approach to lexicon induction for low-resource languages. / Wushouer, Mairidan; Lin, Donghui; Ishida, Toru; Murakami, Yohei.
Cognitive Technologies. 9789811077920. ed. Springer-Verlag, 2018. p. 109-123 (Cognitive Technologies; No. 9789811077920).Research output: Chapter in Book/Report/Conference proceeding › Chapter
}
TY - CHAP
T1 - A constraint approach to lexicon induction for low-resource languages
AU - Wushouer, Mairidan
AU - Lin, Donghui
AU - Ishida, Toru
AU - Murakami, Yohei
PY - 2018/1/1
Y1 - 2018/1/1
N2 - Bilingual lexicon is a useful language resource, but such data rarely available for lower-density language pairs, especially for those that are closely related. The lack or absence of parallel and comparable corpora makes bilingual lexicon extraction becomes a difficult task. Using a third language to link two other languages is a well-known solution in low-resource situation, which usually requires only two input bilingual lexicons to automatically induce the new one. This approach, however, is weak in measuring semantic distance between bilingual word pairs because it has never been demonstrated to utilize the complete structures of the input bilingual lexicons as dropped meanings negatively influence the result. This research discuss a constraint approach to pivot-based lexicon induction in case the target language pair are closely related. We create constraints from language similarity and model the structures of the input dictionaries as an optimization problem whose solution produces optimally correct target bilingual lexicon. In addition, we enable created bilingual lexicons of low-resource languages accessible through service grid federation.
AB - Bilingual lexicon is a useful language resource, but such data rarely available for lower-density language pairs, especially for those that are closely related. The lack or absence of parallel and comparable corpora makes bilingual lexicon extraction becomes a difficult task. Using a third language to link two other languages is a well-known solution in low-resource situation, which usually requires only two input bilingual lexicons to automatically induce the new one. This approach, however, is weak in measuring semantic distance between bilingual word pairs because it has never been demonstrated to utilize the complete structures of the input bilingual lexicons as dropped meanings negatively influence the result. This research discuss a constraint approach to pivot-based lexicon induction in case the target language pair are closely related. We create constraints from language similarity and model the structures of the input dictionaries as an optimization problem whose solution produces optimally correct target bilingual lexicon. In addition, we enable created bilingual lexicons of low-resource languages accessible through service grid federation.
KW - Bilingual dictionary induction
KW - Constraint satisfaction problem
KW - Low-resource languages
KW - Pivot language
KW - Weighted partial max-SAT
UR - http://www.scopus.com/inward/record.url?scp=85042561824&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85042561824&partnerID=8YFLogxK
U2 - 10.1007/978-981-10-7793-7_7
DO - 10.1007/978-981-10-7793-7_7
M3 - Chapter
AN - SCOPUS:85042561824
T3 - Cognitive Technologies
SP - 109
EP - 123
BT - Cognitive Technologies
PB - Springer-Verlag
ER -