Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Sari, Sakayo Toadoum"'
Autor:
Wang, Jiayi, Adelani, David Ifeoluwa, Agrawal, Sweta, Masiak, Marek, Rei, Ricardo, Briakou, Eleftheria, Carpuat, Marine, He, Xuanli, Bourhim, Sofia, Bukula, Andiswa, Mohamed, Muhidin, Olatoye, Temitayo, Adewumi, Tosin, Mokayed, Hamam, Mwase, Christine, Kimotho, Wangui, Yuehgoh, Foutse, Aremu, Anuoluwapo, Ojo, Jessica, Muhammad, Shamsuddeen Hassan, Osei, Salomey, Omotayo, Abdul-Hakeem, Chukwuneke, Chiamaka, Ogayo, Perez, Hourrane, Oumaima, Anigri, Salma El, Ndolela, Lolwethu, Mangwana, Thabiso, Mohamed, Shafie Abdi, Hassan, Ayinde, Awoyomi, Oluwabusayo Olufunke, Alkhaled, Lama, Al-Azzawi, Sana, Etori, Naome A., Ochieng, Millicent, Siro, Clemencia, Njoroge, Samuel, Muchiri, Eric, Kimotho, Wangari, Momo, Lyse Naomi Wamba, Abolade, Daud, Ajao, Simbiat, Shode, Iyanuoluwa, Macharm, Ricky, Iro, Ruqayya Nasir, Abdullahi, Saheed S., Moore, Stephen E., Opoku, Bernard, Akinjobi, Zainab, Afolabi, Abeeb, Obiefuna, Nnaemeka, Ogbu, Onyekachi Raphael, Brian, Sam, Otiende, Verrah Akinyi, Mbonu, Chinedu Emmanuel, Sari, Sakayo Toadoum, Lu, Yao, Stenetorp, Pontus
Despite the recent progress on scaling multilingual machine translation (MT) to several under-resourced African languages, accurately measuring this progress remains challenging, since evaluation is often performed on n-gram matching metrics such as
Externí odkaz:
http://arxiv.org/abs/2311.09828
In Africa, and the world at large, there is an increasing focus on developing Neural Machine Translation (NMT) systems to overcome language barriers. NMT for Low-resource language is particularly compelling as it involves learning with limited labell
Externí odkaz:
http://arxiv.org/abs/2308.13497
Autor:
Adelani, David Ifeoluwa, Chukwuneke, Chiamaka I., Masiak, Marek, Azime, Israel Abebe, Alabi, Jesujoba Oluwadara, Tonja, Atnafu Lambebo, Mwase, Christine, Ogundepo, Odunayo, Dossou, Bonaventure F. P., Oladipo, Akintunde, Nixdorf, Doreen, Emezue, Chris Chinenye, al-azzawi, Sana Sabah, Sibanda, Blessing K., David, Davis, Ndolela, Lolwethu, Mukiibi, Jonathan, Ajayi, Tunde Oluwaseyi, Ngoli, Tatiana Moteu, Odhiambo, Brian, Mbonu, Chinedu E., Owodunni, Abraham Toluwase, Obiefuna, Nnaemeka C., Muhammad, Shamsuddeen Hassan, Abdullahi, Saheed Salahudeen, Yigezu, Mesay Gemeda, Gwadabe, Tajuddeen, Abdulmumin, Idris, Bame, Mahlet Taye, Awoyomi, Oluwabusayo Olufunke, Shode, Iyanuoluwa, Adelani, Tolulope Anu, Kailani, Habiba Abdulganiy, Omotayo, Abdul-Hakeem, Adeeko, Adetola, Abeeb, Afolabi, Aremu, Anuoluwapo, Samuel, Olanrewaju, Siro, Clemencia, Kimotho, Wangari, Ogbu, Onyekachi Raphael, Fanijo, Samuel, Ojo, Jessica, Awosan, Oyinkansola F., Guge, Tadesse Kebede, Sari, Sakayo Toadoum, Nyatsine, Pamela, Sidume, Freedmore, Yousuf, Oreen, Oduwole, Mardiyyah, Kimanuka, Ussen, Tshinu, Kanda Patrick, Diko, Thina, Nxakama, Siyanda, Johar, Abdulmejid Tuni, Gebre, Sinodos, Mohamed, Muhidin, Mohamed, Shafie Abdi, Hassan, Fuad Mire, Mehamed, Moges Ahmed, Ngabire, Evrard, Stenetorp, Pontus
African languages are severely under-represented in NLP research due to lack of datasets covering several NLP tasks. While there are individual language specific datasets that are being expanded to different tasks, only a handful of NLP tasks (e.g. n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______201::13839405a34041c18578faf635780e59
https://eprints.lancs.ac.uk/id/eprint/194287/
https://eprints.lancs.ac.uk/id/eprint/194287/
Autor:
Adelani, David Ifeoluwa, Masiak, Marek, Azime, Israel Abebe, Alabi, Jesujoba Oluwadara, Tonja, Atnafu Lambebo, Mwase, Christine, Ogundepo, Odunayo, Dossou, Bonaventure F. P., Oladipo, Akintunde, Nixdorf, Doreen, Emezue, Chris Chinenye, al-azzawi, Sana Sabah, Sibanda, Blessing K., David, Davis, Ndolela, Lolwethu, Mukiibi, Jonathan, Ajayi, Tunde Oluwaseyi, Ngoli, Tatiana Moteu, Odhiambo, Brian, Owodunni, Abraham Toluwase, Obiefuna, Nnaemeka C., Muhammad, Shamsuddeen Hassan, Abdullahi, Saheed Salahudeen, Yigezu, Mesay Gemeda, Gwadabe, Tajuddeen, Abdulmumin, Idris, Bame, Mahlet Taye, Awoyomi, Oluwabusayo Olufunke, Shode, Iyanuoluwa, Adelani, Tolulope Anu, Kailani, Habiba Abdulganiy, Omotayo, Abdul-Hakeem, Adeeko, Adetola, Abeeb, Afolabi, Aremu, Anuoluwapo, Samuel, Olanrewaju, Siro, Clemencia, Kimotho, Wangari, Ogbu, Onyekachi Raphael, Mbonu, Chinedu E., Chukwuneke, Chiamaka I., Fanijo, Samuel, Ojo, Jessica, Awosan, Oyinkansola F., Guge, Tadesse Kebede, Sari, Sakayo Toadoum, Nyatsine, Pamela, Sidume, Freedmore, Yousuf, Oreen, Oduwole, Mardiyyah, Kimanuka, Ussen, Tshinu, Kanda Patrick, Diko, Thina, Nxakama, Siyanda, Johar, Abdulmejid Tuni, Gebre, Sinodos, Mohamed, Muhidin, Mohamed, Shafie Abdi, Hassan, Fuad Mire, Mehamed, Moges Ahmed, Ngabire, Evrard, Stenetorp, Pontus
African languages are severely under-represented in NLP research due to lack of datasets covering several NLP tasks. While there are individual language specific datasets that are being expanded to different tasks, only a handful of NLP tasks (e.g. n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ee145cc7acb8287a7da138577688db0e
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