Abdallah Bashir

Abdallah Bashir

Universität des Saarlandes

H-index: 3

Europe-Germany

About Abdallah Bashir

Abdallah Bashir, With an exceptional h-index of 3 and a recent h-index of 3 (since 2020), a distinguished researcher at Universität des Saarlandes, specializes in the field of NLP, AI, Neural Networks.

His recent articles reflect a diverse array of research interests and contributions to the field:

Masakhane--Machine Translation For Africa

Participatory research for low-resourced machine translation: A case study in african languages

Abdallah Bashir Information

University

Universität des Saarlandes

Position

___

Citations(all)

191

Citations(since 2020)

191

Cited By

25

hIndex(all)

3

hIndex(since 2020)

3

i10Index(all)

3

i10Index(since 2020)

3

Email

University Profile Page

Universität des Saarlandes

Abdallah Bashir Skills & Research Interests

NLP

AI

Neural Networks

Top articles of Abdallah Bashir

Masakhane--Machine Translation For Africa

Authors

Iroro Orife,Julia Kreutzer,Blessing Sibanda,Daniel Whitenack,Kathleen Siminyu,Laura Martinus,Jamiil Toure Ali,Jade Abbott,Vukosi Marivate,Salomon Kabongo,Musie Meressa,Espoir Murhabazi,Orevaoghene Ahia,Elan Van Biljon,Arshath Ramkilowan,Adewale Akinfaderin,Alp Öktem,Wole Akin,Ghollah Kioko,Kevin Degila,Herman Kamper,Bonaventure Dossou,Chris Emezue,Kelechi Ogueji,Abdallah Bashir

Journal

arXiv preprint arXiv:2003.11529

Published Date

2020/3/13

Africa has over 2000 languages. Despite this, African languages account for a small portion of available resources and publications in Natural Language Processing (NLP). This is due to multiple factors, including: a lack of focus from government and funding, discoverability, a lack of community, sheer language complexity, difficulty in reproducing papers and no benchmarks to compare techniques. To begin to address the identified problems, MASAKHANE, an open-source, continent-wide, distributed, online research effort for machine translation for African languages, was founded. In this paper, we discuss our methodology for building the community and spurring research from the African continent, as well as outline the success of the community in terms of addressing the identified problems affecting African NLP.

Participatory research for low-resourced machine translation: A case study in african languages

Authors

Wilhelmina Nekoto,Vukosi Marivate,Tshinondiwa Matsila,Timi Fasubaa,Tajudeen Kolawole,Taiwo Fagbohungbe,Solomon Oluwole Akinola,Shamsuddeen Hassan Muhammad,Salomon Kabongo,Salomey Osei,Sackey Freshia,Rubungo Andre Niyongabo,Ricky Macharm,Perez Ogayo,Orevaoghene Ahia,Musie Meressa,Mofe Adeyemi,Masabata Mokgesi-Selinga,Lawrence Okegbemi,Laura Jane Martinus,Kolawole Tajudeen,Kevin Degila,Kelechi Ogueji,Kathleen Siminyu,Julia Kreutzer,Jason Webster,Jamiil Toure Ali,Jade Abbott,Iroro Orife,Ignatius Ezeani,Idris Abdulkabir Dangana,Herman Kamper,Hady Elsahar,Goodness Duru,Ghollah Kioko,Espoir Murhabazi,Elan Van Biljon,Daniel Whitenack,Christopher Onyefuluchi,Chris Emezue,Bonaventure Dossou,Blessing Sibanda,Blessing Itoro Bassey,Ayodele Olabiyi,Arshath Ramkilowan,Alp Öktem,Adewale Akinfaderin,Abdallah Bashir

Journal

arXiv preprint arXiv:2010.02353

Published Date

2020/10/5

Research in NLP lacks geographic diversity, and the question of how NLP can be scaled to low-resourced languages has not yet been adequately solved. "Low-resourced"-ness is a complex problem going beyond data availability and reflects systemic problems in society. In this paper, we focus on the task of Machine Translation (MT), that plays a crucial role for information accessibility and communication worldwide. Despite immense improvements in MT over the past decade, MT is centered around a few high-resourced languages. As MT researchers cannot solve the problem of low-resourcedness alone, we propose participatory research as a means to involve all necessary agents required in the MT development process. We demonstrate the feasibility and scalability of participatory research with a case study on MT for African languages. Its implementation leads to a collection of novel translation datasets, MT benchmarks for over 30 languages, with human evaluations for a third of them, and enables participants without formal training to make a unique scientific contribution. Benchmarks, models, data, code, and evaluation results are released under https://github.com/masakhane-io/masakhane-mt.

See List of Professors in Abdallah Bashir University(Universität des Saarlandes)

Abdallah Bashir FAQs

What is Abdallah Bashir's h-index at Universität des Saarlandes?

The h-index of Abdallah Bashir has been 3 since 2020 and 3 in total.

What are Abdallah Bashir's top articles?

The articles with the titles of

Masakhane--Machine Translation For Africa

Participatory research for low-resourced machine translation: A case study in african languages

are the top articles of Abdallah Bashir at Universität des Saarlandes.

What are Abdallah Bashir's research interests?

The research interests of Abdallah Bashir are: NLP, AI, Neural Networks

What is Abdallah Bashir's total number of citations?

Abdallah Bashir has 191 citations in total.

What are the co-authors of Abdallah Bashir?

The co-authors of Abdallah Bashir are Benjamin Rosman.

    Co-Authors

    H-index: 23
    Benjamin Rosman

    Benjamin Rosman

    University of the Witwatersrand

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