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Crowdsourcing a text corpus for a low resource language
Low resourced languages, such as South Africa's isiXhosa, have a limited number of digitised texts, making it challenging to build language corpora and the information retrieval services, such as search and translation that depend on them. Researchers have been unable to assemble isiXhosa corpora of...
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| Format: | Thesis |
| Language: | English |
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Department of Computer Science
2016
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| _version_ | 1867614047907610624 |
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| access_status_str | Open Access |
| author | Packham, Sean |
| author2 | Suleman, Hussein |
| author_browse | Packham, Sean Suleman, Hussein |
| author_facet | Suleman, Hussein Packham, Sean |
| author_sort | Packham, Sean |
| collection | Thesis |
| description | Low resourced languages, such as South Africa's isiXhosa, have a limited number of digitised texts, making it challenging to build language corpora and the information retrieval services, such as search and translation that depend on them. Researchers have been unable to assemble isiXhosa corpora of sufficient size and quality to produce working machine translation systems and it has been acknowledged that there is little to know training data and sourcing translations from professionals can be a costly process. A crowdsourcing translation game which paid participants for their contributions was proposed as a solution to source original and relevant parallel corpora for low resource languages such as isiXhosa. The objectives of this dissertation is to report on the four experiments that were conducted to assess user motivation and contribution quantity under various scenarios using the developed crowdsourcing translation game. The first experiment was a pilot study to test a custom built system and to find out if social network users would volunteer to participate in a translation game for free. The second experiment tested multiple payment schemes with users from the University of Cape Town. The schemes rewarded users with consistent, increasing or decreasing amounts for subsequent contributions. Experiment 3 tested whether the same users from Experiment 2 would continue contributing if payments were taken away. The last experiment tested a payment scheme that did not offer a direct and guaranteed reward. Users were paid based on their leaderboard placement and only a limited number of the top leaderboard spots were allocated rewards. From experiment 1 and 3 we found that people do not volunteer without financial incentives, experiment 2 and 4 showed that people want increased rewards when putting in increased effort , experiment 3 also showed that people will not continue contributing if the financial incentives are taken away and experiment 4 also showed that the possibility of incentives is as attractive as offering guaranteed incentives . |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/20436 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:45:50.449Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2016 |
| publishDateRange | 2016 |
| publishDateSort | 2016 |
| publisher | Department of Computer Science |
| publisherStr | Department of Computer Science |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/20436 Crowdsourcing a text corpus for a low resource language Packham, Sean Suleman, Hussein Computer Science Low resourced languages, such as South Africa's isiXhosa, have a limited number of digitised texts, making it challenging to build language corpora and the information retrieval services, such as search and translation that depend on them. Researchers have been unable to assemble isiXhosa corpora of sufficient size and quality to produce working machine translation systems and it has been acknowledged that there is little to know training data and sourcing translations from professionals can be a costly process. A crowdsourcing translation game which paid participants for their contributions was proposed as a solution to source original and relevant parallel corpora for low resource languages such as isiXhosa. The objectives of this dissertation is to report on the four experiments that were conducted to assess user motivation and contribution quantity under various scenarios using the developed crowdsourcing translation game. The first experiment was a pilot study to test a custom built system and to find out if social network users would volunteer to participate in a translation game for free. The second experiment tested multiple payment schemes with users from the University of Cape Town. The schemes rewarded users with consistent, increasing or decreasing amounts for subsequent contributions. Experiment 3 tested whether the same users from Experiment 2 would continue contributing if payments were taken away. The last experiment tested a payment scheme that did not offer a direct and guaranteed reward. Users were paid based on their leaderboard placement and only a limited number of the top leaderboard spots were allocated rewards. From experiment 1 and 3 we found that people do not volunteer without financial incentives, experiment 2 and 4 showed that people want increased rewards when putting in increased effort , experiment 3 also showed that people will not continue contributing if the financial incentives are taken away and experiment 4 also showed that the possibility of incentives is as attractive as offering guaranteed incentives . 2016-07-18T12:55:04Z 2016-07-18T12:55:04Z 2016 Master Thesis Masters MSc http://hdl.handle.net/11427/20436 eng application/pdf Department of Computer Science Faculty of Science University of Cape Town |
| spellingShingle | Computer Science Packham, Sean Crowdsourcing a text corpus for a low resource language |
| thesis_degree_str | Master's |
| title | Crowdsourcing a text corpus for a low resource language |
| title_full | Crowdsourcing a text corpus for a low resource language |
| title_fullStr | Crowdsourcing a text corpus for a low resource language |
| title_full_unstemmed | Crowdsourcing a text corpus for a low resource language |
| title_short | Crowdsourcing a text corpus for a low resource language |
| title_sort | crowdsourcing a text corpus for a low resource language |
| topic | Computer Science |
| url | http://hdl.handle.net/11427/20436 |
| work_keys_str_mv | AT packhamsean crowdsourcingatextcorpusforalowresourcelanguage |