dc.contributor.author |
Bhattacharyya, P |
|
dc.contributor.author |
Murthy, H |
|
dc.contributor.author |
Ranathunga, S |
|
dc.contributor.author |
Munasinghe, R |
|
dc.date.accessioned |
2023-03-27T05:41:21Z |
|
dc.date.available |
2023-03-27T05:41:21Z |
|
dc.date.issued |
2019 |
|
dc.identifier.citation |
Bhattacharyya, P., Murthy, H., Ranathunga, S., & Munasinghe, R. (2019). Indic language computing. Communications of the ACM, 62(11), 70–75. https://doi.org/10.1145/3343456 |
en_US |
dc.identifier.issn |
0001-0782 |
en_US |
dc.identifier.uri |
http://dl.lib.uom.lk/handle/123/20817 |
|
dc.description.abstract |
In April 2019, following the Easter Sunday bomb attacks, the Government of Sri Lanka had to shut down Facebook and YouTube for nine days to stop the spreading of hate speech and false news, posted mainly in the local languages Sinhala and Tamil. This came about simply because these social media platforms did not have the capability to detect and warn about the provocative content.
India's Ministry of Human Resource Development (MHRD) wants lectures on Swayama and NPTELb—the online teaching platforms—to be translated into all Indian languages. Approximately 2.5 million students use the Swayam lectures on computer science alone. The lectures are in English, which students find difficult to understand. A large number of lectures are manually subtitled in English. Automatic speech recognition and machine translation into Indian languages will be great enablers for the marginalized sections of society. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
Association for Computing Machinery |
en_US |
dc.title |
Indic language computing |
en_US |
dc.type |
Article-Full-text |
en_US |
dc.identifier.year |
2019 |
en_US |
dc.identifier.journal |
Communications of the ACM |
en_US |
dc.identifier.issue |
11 |
en_US |
dc.identifier.volume |
62 |
en_US |
dc.identifier.pgnos |
70-75 |
en_US |
dc.identifier.doi |
10.1145/3343456 |
en_US |