Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Tapo, Allahsera"'
In the last 5 years, the availability of large audio datasets in African countries has opened unlimited opportunities to build machine intelligence (MI) technologies that are closer to the people and speak, learn, understand, and do businesses in loc
Externí odkaz:
http://arxiv.org/abs/2402.02218
Autor:
Dione, Cheikh M. Bamba, Adelani, David, Nabende, Peter, Alabi, Jesujoba, Sindane, Thapelo, Buzaaba, Happy, Muhammad, Shamsuddeen Hassan, Emezue, Chris Chinenye, Ogayo, Perez, Aremu, Anuoluwapo, Gitau, Catherine, Mbaye, Derguene, Mukiibi, Jonathan, Sibanda, Blessing, Dossou, Bonaventure F. P., Bukula, Andiswa, Mabuya, Rooweither, Tapo, Allahsera Auguste, Munkoh-Buabeng, Edwin, Koagne, victoire Memdjokam, Kabore, Fatoumata Ouoba, Taylor, Amelia, Kalipe, Godson, Macucwa, Tebogo, Marivate, Vukosi, Gwadabe, Tajuddeen, Elvis, Mboning Tchiaze, Onyenwe, Ikechukwu, Atindogbe, Gratien, Adelani, Tolulope, Akinade, Idris, Samuel, Olanrewaju, Nahimana, Marien, Musabeyezu, Théogène, Niyomutabazi, Emile, Chimhenga, Ester, Gotosa, Kudzai, Mizha, Patrick, Agbolo, Apelete, Traore, Seydou, Uchechukwu, Chinedu, Yusuf, Aliyu, Abdullahi, Muhammad, Klakow, Dietrich
In this paper, we present MasakhaPOS, the largest part-of-speech (POS) dataset for 20 typologically diverse African languages. We discuss the challenges in annotating POS for these languages using the UD (universal dependencies) guidelines. We conduc
Externí odkaz:
http://arxiv.org/abs/2305.13989
Autor:
Adelani, David Ifeoluwa, Neubig, Graham, Ruder, Sebastian, Rijhwani, Shruti, Beukman, Michael, Palen-Michel, Chester, Lignos, Constantine, Alabi, Jesujoba O., Muhammad, Shamsuddeen H., Nabende, Peter, Dione, Cheikh M. Bamba, Bukula, Andiswa, Mabuya, Rooweither, Dossou, Bonaventure F. P., Sibanda, Blessing, Buzaaba, Happy, Mukiibi, Jonathan, Kalipe, Godson, Mbaye, Derguene, Taylor, Amelia, Kabore, Fatoumata, Emezue, Chris Chinenye, Aremu, Anuoluwapo, Ogayo, Perez, Gitau, Catherine, Munkoh-Buabeng, Edwin, Koagne, Victoire M., Tapo, Allahsera Auguste, Macucwa, Tebogo, Marivate, Vukosi, Mboning, Elvis, Gwadabe, Tajuddeen, Adewumi, Tosin, Ahia, Orevaoghene, Nakatumba-Nabende, Joyce, Mokono, Neo L., Ezeani, Ignatius, Chukwuneke, Chiamaka, Adeyemi, Mofetoluwa, Hacheme, Gilles Q., Abdulmumin, Idris, Ogundepo, Odunayo, Yousuf, Oreen, Ngoli, Tatiana Moteu, Klakow, Dietrich
African languages are spoken by over a billion people, but are underrepresented in NLP research and development. The challenges impeding progress include the limited availability of annotated datasets, as well as a lack of understanding of the settin
Externí odkaz:
http://arxiv.org/abs/2210.12391
Autor:
Adelani, David Ifeoluwa, Alabi, Jesujoba Oluwadara, Fan, Angela, Kreutzer, Julia, Shen, Xiaoyu, Reid, Machel, Ruiter, Dana, Klakow, Dietrich, Nabende, Peter, Chang, Ernie, Gwadabe, Tajuddeen, Sackey, Freshia, Dossou, Bonaventure F. P., Emezue, Chris Chinenye, Leong, Colin, Beukman, Michael, Muhammad, Shamsuddeen Hassan, Jarso, Guyo Dub, Yousuf, Oreen, Rubungo, Andre Niyongabo, Hacheme, Gilles, Wairagala, Eric Peter, Nasir, Muhammad Umair, Ajibade, Benjamin Ayoade, Ajayi, Tunde Oluwaseyi, Gitau, Yvonne Wambui, Abbott, Jade, Ahmed, Mohamed, Ochieng, Millicent, Aremu, Anuoluwapo, Ogayo, Perez, Mukiibi, Jonathan, Kabore, Fatoumata Ouoba, Kalipe, Godson Koffi, Mbaye, Derguene, Tapo, Allahsera Auguste, Koagne, Victoire Memdjokam, Munkoh-Buabeng, Edwin, Wagner, Valencia, Abdulmumin, Idris, Awokoya, Ayodele, Buzaaba, Happy, Sibanda, Blessing, Bukula, Andiswa, Manthalu, Sam
Recent advances in the pre-training of language models leverage large-scale datasets to create multilingual models. However, low-resource languages are mostly left out in these datasets. This is primarily because many widely spoken languages are not
Externí odkaz:
http://arxiv.org/abs/2205.02022
Autor:
Tapo, Allahsera Auguste, Leventhal, Michael, Luger, Sarah, Homan, Christopher M., Zampieri, Marcos
Translating to and from low-resource languages is a challenge for machine translation (MT) systems due to a lack of parallel data. In this paper we address the issue of domain-specific MT for Bambara, an under-resourced Mande language spoken in Mali.
Externí odkaz:
http://arxiv.org/abs/2104.00041
Autor:
Kreutzer, Julia, Caswell, Isaac, Wang, Lisa, Wahab, Ahsan, van Esch, Daan, Ulzii-Orshikh, Nasanbayar, Tapo, Allahsera, Subramani, Nishant, Sokolov, Artem, Sikasote, Claytone, Setyawan, Monang, Sarin, Supheakmungkol, Samb, Sokhar, Sagot, Benoît, Rivera, Clara, Rios, Annette, Papadimitriou, Isabel, Osei, Salomey, Suarez, Pedro Ortiz, Orife, Iroro, Ogueji, Kelechi, Rubungo, Andre Niyongabo, Nguyen, Toan Q., Müller, Mathias, Müller, André, Muhammad, Shamsuddeen Hassan, Muhammad, Nanda, Mnyakeni, Ayanda, Mirzakhalov, Jamshidbek, Matangira, Tapiwanashe, Leong, Colin, Lawson, Nze, Kudugunta, Sneha, Jernite, Yacine, Jenny, Mathias, Firat, Orhan, Dossou, Bonaventure F. P., Dlamini, Sakhile, de Silva, Nisansa, Ballı, Sakine Çabuk, Biderman, Stella, Battisti, Alessia, Baruwa, Ahmed, Bapna, Ankur, Baljekar, Pallavi, Azime, Israel Abebe, Awokoya, Ayodele, Ataman, Duygu, Ahia, Orevaoghene, Ahia, Oghenefego, Agrawal, Sweta, Adeyemi, Mofetoluwa
Publikováno v:
Transactions of the Association for Computational Linguistics (2022) 10: 50-72
With the success of large-scale pre-training and multilingual modeling in Natural Language Processing (NLP), recent years have seen a proliferation of large, web-mined text datasets covering hundreds of languages. We manually audit the quality of 205
Externí odkaz:
http://arxiv.org/abs/2103.12028
Autor:
Tapo, Allahsera Auguste, Coulibaly, Bakary, Diarra, Sébastien, Homan, Christopher, Kreutzer, Julia, Luger, Sarah, Nagashima, Arthur, Zampieri, Marcos, Leventhal, Michael
Low-resource languages present unique challenges to (neural) machine translation. We discuss the case of Bambara, a Mande language for which training data is scarce and requires significant amounts of pre-processing. More than the linguistic situatio
Externí odkaz:
http://arxiv.org/abs/2011.05284
We present novel methods for assessing the quality of human-translated aligned texts for learning machine translation models of under-resourced languages. Malian university students translated French texts, producing either written or oral translatio
Externí odkaz:
http://arxiv.org/abs/2004.00068
Autor:
Kreutzer, Julia, Caswell, Isaac, Wang, Lisa, Wahab, Ahsan, van Esch, Daan, Ulzii-Orshikh, Nasanbayar, Tapo, Allahsera, Subramani, Nishant, Sokolov, Artem, Sikasote, Claytone, Setyawan, Monang, Sarin, Supheakmungkol, Samb, Sokhar, Sagot, Benoît, Rivera, Clara, Rios, Annette, Papadimitriou, Isabel, Osei, Salomey, Suarez, Pedro Ortiz, Orife, Iroro, Ogueji, Kelechi, Rubungo, Andre Niyongabo, Nguyen, Toan Q., Müller, Mathias, Müller, André, Muhammad, Shamsuddeen Hassan, Muhammad, Nanda, Mnyakeni, Ayanda, Mirzakhalov, Jamshidbek, Matangira, Tapiwanashe, Leong, Colin, Lawson, Nze, Kudugunta, Sneha, Jernite, Yacine, Jenny, Mathias, Firat, Orhan, Dossou, Bonaventure F. P., Dlamini, Sakhile, de Silva, Nisansa, Ballı, Sakine Çabuk, Biderman, Stella, Battisti, Alessia, Baruwa, Ahmed, Bapna, Ankur, Baljekar, Pallavi, Azime, Israel Abebe, Awokoya, Ayodele, Ataman, Duygu, Ahia, Orevaoghene, Ahia, Oghenefego, Agrawal, Sweta, Adeyemi, Mofetoluwa
Publikováno v:
Transactions of the Association for Computational Linguistics
Transactions of the Association for Computational Linguistics, 2022, 10, pp.50-72. ⟨10.1162/tacl_a_00447⟩
Transactions of the Association for Computational Linguistics, 2022, 10, pp.50-72. ⟨10.1162/tacl_a_00447⟩
With the success of large-scale pre-training and multilingual modeling in Natural Language Processing (NLP), recent years have seen a proliferation of large, web-mined text datasets covering hundreds of languages. We manually audit the quality of 205