Search Results - "Etori, Naome"

AfriSpeech-200: Pan-African Accented Speech Dataset for Clinical and General Domain ASR by Olatunji, Tobi, Afonja, Tejumade, Yadavalli, Aditya, Emezue, Chris Chinenye, Singh, Sahib, Dossou, Bonaventure F. P., Osuchukwu, Joanne, Osei, Salomey, Tonja, Atnafu Lambebo, Etori, Naome, Mbataku, Clinton

“…Abstract Africa has a very poor doctor-to-patient ratio. At very busy clinics, doctors could see 30+ patients per day—a heavy patient burden compared with…”
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What We Know So Far: Artificial Intelligence in African Healthcare by Etori, Naome, Temesgen, Ebasa, Gini, Maria

“…Healthcare in Africa is a complex issue influenced by many factors including poverty, lack of infrastructure, and inadequate funding. However, Artificial…”
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User or Labor: An Interaction Framework for Human-Machine Relationships in NLP by Wan, Ruyuan, Etori, Naome, Badillo-Urquiola, Karla, Kang, Dongyeop

“…The bridging research between Human-Computer Interaction and Natural Language Processing is developing quickly these years. However, there is still a lack of…”
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Performant ASR Models for Medical Entities in Accented Speech by Afonja, Tejumade, Olatunji, Tobi, Ogun, Sewade, Etori, Naome A, Owodunni, Abraham, Yekini, Moshood

“…Recent strides in automatic speech recognition (ASR) have accelerated their application in the medical domain where their performance on accented medical named…”
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TEXT2TASTE: A Versatile Egocentric Vision System for Intelligent Reading Assistance Using Large Language Model by Mucha, Wiktor, Cuconasu, Florin, Etori, Naome A, Kalokyri, Valia, Trappolini, Giovanni

“…The ability to read, understand and find important information from written text is a critical skill in our daily lives for our independence, comfort and…”
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1000 African Voices: Advancing inclusive multi-speaker multi-accent speech synthesis by Ogun, Sewade, Owodunni, Abraham T, Olatunji, Tobi, Alese, Eniola, Oladimeji, Babatunde, Afonja, Tejumade, Olaleye, Kayode, Etori, Naome A, Adewumi, Tosin

“…Recent advances in speech synthesis have enabled many useful applications like audio directions in Google Maps, screen readers, and automated content…”
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The State of Computer Vision Research in Africa by Omotayo, Abdul-Hakeem, Mbilinyi, Ashery, Ismaila, Lukman, Turki, Houcemeddine, Mahmoud Abdien, Karim Gamal, Idriss Tondji, Yvan Pimi, Naome A. Etori, Marwa M. Matar, Clifford Broni-Bediako, Abigail Oppong, Mai Gamal, Eman Ehab, Gbetondji Dovonon, Zainab Akinjobi, Daniel Ajisafe, Oluwabukola G. Adegboro, Mennatullah Siam

“…Despite significant efforts to democratize artificial intelligence (AI), computer vision which is a sub-field of AI, still lags in Africa. A significant factor…”
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Text Categorization Can Enhance Domain-Agnostic Stopword Extraction by Turki, Houcemeddine, Etori, Naome A, Taieb, Mohamed Ali Hadj, Omotayo, Abdul-Hakeem, Emezue, Chris Chinenye, Aouicha, Mohamed Ben, Awokoya, Ayodele, Lawan, Falalu Ibrahim, Nixdorf, Doreen

“…This paper investigates the role of text categorization in streamlining stopword extraction in natural language processing (NLP), specifically focusing on nine…”
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State of NLP in Kenya: A Survey by Amol, Cynthia Jayne, Chimoto, Everlyn Asiko, Gesicho, Rose Delilah, Gitau, Antony M, Etori, Naome A, Kinyanjui, Caringtone, Ndung'u, Steven, Moruye, Lawrence, Ooko, Samson Otieno, Kitonga, Kavengi, Muhia, Brian, Gitau, Catherine, Ndolo, Antony, Wanzare, Lilian D. A, Kahira, Albert Njoroge, Tombe, Ronald

“…Kenya, known for its linguistic diversity, faces unique challenges and promising opportunities in advancing Natural Language Processing (NLP) technologies,…”
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AfriSpeech-200: Pan-African Accented Speech Dataset for Clinical and General Domain ASR by Olatunji, Tobi, Afonja, Tejumade, Yadavalli, Aditya, Emezue, Chris Chinenye, Singh, Sahib, Dossou, Bonaventure F. P, Osuchukwu, Joanne, Osei, Salomey, Tonja, Atnafu Lambebo, Etori, Naome, Mbataku, Clinton

“…Africa has a very low doctor-to-patient ratio. At very busy clinics, doctors could see 30+ patients per day -- a heavy patient burden compared with developed…”
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Krey\`ol-MT: Building MT for Latin American, Caribbean and Colonial African Creole Languages by Robinson, Nathaniel R, Dabre, Raj, Shurtz, Ammon, Dent, Rasul, Onesi, Onenamiyi, Monroc, Claire Bizon, Grobol, Loïc, Muhammad, Hasan, Garg, Ashi, Etori, Naome A, Tiyyala, Vijay Murari, Samuel, Olanrewaju, Stutzman, Matthew Dean, Odoom, Bismarck Bamfo, Khudanpur, Sanjeev, Richardson, Stephen D, Murray, Kenton

“…A majority of language technologies are tailored for a small number of high-resource languages, while relatively many low-resource languages are neglected. One…”
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The State of Computer Vision Research in Africa by Omotayo, Abdul-Hakeem, Mbilinyi, Ashery, Ismaila, Lukman, Turki, Houcemeddine, Abdien, Mahmoud, Gamal, Karim, Tondji, Idriss, Pimi, Yvan, Etori, Naome A, Matar, Marwa M, Broni-Bediako, Clifford, Oppong, Abigail, Gamal, Mai, Ehab, Eman, Dovonon, Gbetondji, Akinjobi, Zainab, Ajisafe, Daniel, Adegboro, Oluwabukola G, Siam, Mennatullah

“…JAIR 2024 Despite significant efforts to democratize artificial intelligence (AI), computer vision which is a sub-field of AI, still lags in Africa. A…”
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The African Stopwords project: curating stopwords for African languages by Emezue, Chris, Nigatu, Hellina, Thinwa, Cynthia, Zhou, Helper, Muhammad, Shamsuddeen, Louis, Lerato, Abdulmumin, Idris, Oyerinde, Samuel, Ajibade, Benjamin, Samuel, Olanrewaju, Joshua, Oviawe, Onwuegbuzia, Emeka, Emezue, Handel, Ige, Ifeoluwatayo A, Tonja, Atnafu Lambebo, Chukwuneke, Chiamaka, Dossou, Bonaventure F. P, Etori, Naome A, Emmanuel, Mbonu Chinedu, Yousuf, Oreen, Aina, Kaosarat, David, Davis

“…Stopwords are fundamental in Natural Language Processing (NLP) techniques for information retrieval. One of the common tasks in preprocessing of text data is…”
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AfriMTE and AfriCOMET: Enhancing COMET to Embrace Under-resourced African Languages by 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…”
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