Fuzzy Influenced Process to Generate Comparable to Parallel Corpora
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AGPAWR8UW" target="_blank" >RIV/00216208:11320/23:GPAWR8UW - isvavai.cz</a>
Result on the web
<a href="https://dl.acm.org/doi/10.1145/3599235" target="_blank" >https://dl.acm.org/doi/10.1145/3599235</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3599235" target="_blank" >10.1145/3599235</a>
Alternative languages
Result language
angličtina
Original language name
Fuzzy Influenced Process to Generate Comparable to Parallel Corpora
Original language description
"Data-driven supervised approaches rely on the parallel corpus. Due to lack of data and resources availability, it has become more difficult to achieve accurate outputs. In addition, the efficiency of the machine translation system depends on the quality of the used corpora. Hindi still lacks good quality parallel corpora and needs more resources for accurate machine translation. Comparable corpora are easily available compared to parallel corpora, but they cannot be used directly in machine translation. In our present research, we propose an algorithm to mine these comparable corpora from the web, and generate the parallel corpora automatically. Machine translation systems, system combination approach, and IR-based technique join their hands together to choose the set of sentence pairs. Then the sentence pairs having the best score are chosen to prepare the final parallel corpora. The primary modules of this architecture are fuzzy logic-based evaluation metric, information retrieval module, statistical machine translation system, Google neural machine translation system, Microsoft machine translation system, and system combination module for machine translation. For case study, we prepare the Hindi-English parallel corpora of (30825 + 51235) = 82060 sentence pairs. Evaluation results show that the F-Score measurement varies from 95.73 to 96.98 for various data sets. The source code and prepared dataset (comparable and parallel corpus) can be found at https://github.com/debajyoty/Comparable-partallel-Algo2.git."
Czech name
—
Czech description
—
Classification
Type
J<sub>ost</sub> - Miscellaneous article in a specialist periodical
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
—
Continuities
—
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
"ACM Transactions on Asian and Low-Resource Language Information Processing"
ISSN
2375-4699
e-ISSN
—
Volume of the periodical
""
Issue of the periodical within the volume
2023-12-22
Country of publishing house
US - UNITED STATES
Number of pages
23
Pages from-to
1-23
UT code for WoS article
—
EID of the result in the Scopus database
—