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Laura Martinus – One of the best experts on this subject based on the ideXlab platform.

  • benchmarking neural machine translation for southern African Languages
    Meeting of the Association for Computational Linguistics, 2019
    Co-Authors: Jade Z. Abbott, Laura Martinus

    Abstract:

    Unlike major Western Languages, most African Languages are very low-resourced. Furthermore, the resources that do exist are often scattered and difficult to obtain and discover. As a result, the data and code for existing research has rarely been shared, meaning researchers struggle to reproduce reported results, and almost no publicly available benchmarks or leaderboards for African machine translation models exist. To start to address these problems, we trained neural machine translation models for a subset of Southern African Languages on publicly-available datasets. We provide the code for training the models and evaluate the models on a newly released evaluation set, with the aim of starting a leaderboard for Southern African Languages and spur future research in the field.

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  • Benchmarking Neural Machine Translation for Southern African Languages
    arXiv: Computation and Language, 2019
    Co-Authors: Laura Martinus, Jade Z. Abbott

    Abstract:

    Unlike major Western Languages, most African Languages are very low-resourced. Furthermore, the resources that do exist are often scattered and difficult to obtain and discover. As a result, the data and code for existing research has rarely been shared. This has lead a struggle to reproduce reported results, and few publicly available benchmarks for African machine translation models exist. To start to address these problems, we trained neural machine translation models for 5 Southern African Languages on publicly-available datasets. Code is provided for training the models and evaluate the models on a newly released evaluation set, with the aim of spur future research in the field for Southern African Languages.

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  • WNLP@ACL – Benchmarking Neural Machine Translation for Southern African Languages
    , 2019
    Co-Authors: Jade Z. Abbott, Laura Martinus

    Abstract:

    Unlike major Western Languages, most African Languages are very low-resourced. Furthermore, the resources that do exist are often scattered and difficult to obtain and discover. As a result, the data and code for existing research has rarely been shared, meaning researchers struggle to reproduce reported results, and almost no publicly available benchmarks or leaderboards for African machine translation models exist. To start to address these problems, we trained neural machine translation models for a subset of Southern African Languages on publicly-available datasets. We provide the code for training the models and evaluate the models on a newly released evaluation set, with the aim of starting a leaderboard for Southern African Languages and spur future research in the field.

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Jade Z. Abbott – One of the best experts on this subject based on the ideXlab platform.

  • benchmarking neural machine translation for southern African Languages
    Meeting of the Association for Computational Linguistics, 2019
    Co-Authors: Jade Z. Abbott, Laura Martinus

    Abstract:

    Unlike major Western Languages, most African Languages are very low-resourced. Furthermore, the resources that do exist are often scattered and difficult to obtain and discover. As a result, the data and code for existing research has rarely been shared, meaning researchers struggle to reproduce reported results, and almost no publicly available benchmarks or leaderboards for African machine translation models exist. To start to address these problems, we trained neural machine translation models for a subset of Southern African Languages on publicly-available datasets. We provide the code for training the models and evaluate the models on a newly released evaluation set, with the aim of starting a leaderboard for Southern African Languages and spur future research in the field.

    Free Register to Access Article

  • Benchmarking Neural Machine Translation for Southern African Languages
    arXiv: Computation and Language, 2019
    Co-Authors: Laura Martinus, Jade Z. Abbott

    Abstract:

    Unlike major Western Languages, most African Languages are very low-resourced. Furthermore, the resources that do exist are often scattered and difficult to obtain and discover. As a result, the data and code for existing research has rarely been shared. This has lead a struggle to reproduce reported results, and few publicly available benchmarks for African machine translation models exist. To start to address these problems, we trained neural machine translation models for 5 Southern African Languages on publicly-available datasets. Code is provided for training the models and evaluate the models on a newly released evaluation set, with the aim of spur future research in the field for Southern African Languages.

    Free Register to Access Article

  • WNLP@ACL – Benchmarking Neural Machine Translation for Southern African Languages
    , 2019
    Co-Authors: Jade Z. Abbott, Laura Martinus

    Abstract:

    Unlike major Western Languages, most African Languages are very low-resourced. Furthermore, the resources that do exist are often scattered and difficult to obtain and discover. As a result, the data and code for existing research has rarely been shared, meaning researchers struggle to reproduce reported results, and almost no publicly available benchmarks or leaderboards for African machine translation models exist. To start to address these problems, we trained neural machine translation models for a subset of Southern African Languages on publicly-available datasets. We provide the code for training the models and evaluate the models on a newly released evaluation set, with the aim of starting a leaderboard for Southern African Languages and spur future research in the field.

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Harouna Naroua – One of the best experts on this subject based on the ideXlab platform.

  • Evaluation of Virtual Keyboards for West-African Languages
    , 2017
    Co-Authors: Chantal Enguehard, Harouna Naroua

    Abstract:

    West African Languages are written with alphabets that comprize non classical Latin characters. It is possible to design virtual keyboards which allow the writing of such special characters with a combination of keys. During the last decade, many different virtual keyboards had been created, without any standardization to fix the correspondence between each character and the keys to press to obtain it. We define a grid to evaluate such keyboards and apply it to five virtual keyboards in relation with the five main Languages of Niger (Fulfulde, Hausa, Kanuri, Songhai-Zarma, Tamashek), Bambara and Soninke from Mali and Dyoula from Burkina Faso. We conclude that the African LLACAN keyboard should be recommended in Niger because it covers all the characters used in the alphabets of the main Languages of this country, it produces valid Unicode codes and it minimizes the number of keys to be pressed.

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  • On the Computerization of African Languages
    American Journal of Applied Sciences, 2016
    Co-Authors: Harouna Naroua, Lawaly Salifou

    Abstract:

    In this article, a computer tool for processing African Languages has been designed. It is intended to be a contribution to the automatic processing of African Languages. The current study is focused on West African Languages where five main Languages from Niger, two from Mali and one from Burkina Faso are considered. After a brief review of African Languages processing, we designed a tool which uses minimum resources and operates essentially on a dictionary and the characteristics of the language alphabet. The dictionary is represented using a trie data structure. For the sake of application, the designed tool operates as a spell checker. To detect and correct spelling errors, the edit distance and the specificities of the language are used. Although they do not have processing tools, it was shown that existing tools for computerized Languages can be adapted to African Languages efficiently. To extend the designed tool to any African language, we only need to provide an appropriate dictionary and alphabet.

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  • LREC – Evaluation of Virtual Keyboards for West-African Languages
    , 2008
    Co-Authors: Chantal Enguehard, Harouna Naroua

    Abstract:

    West African Languages are written with alphabets that comprize non classical Latin characters. It is possible to design virtual keyboards which allow the writing of such special characters with a combination of keys. During the last decade, many different virtual keyboards had been created, without any standardization to fix the correspondence between each character and the keys to press to obtain it. We define a grid to evaluate such keyboards and apply it to five virtual keyboards in relation with the five main Languages of Niger (Fulfulde, Hausa, Kanuri, Songhai-Zarma, Tamashek), Bambara and Soninke from Mali and Dyoula from Burkina Faso. We conclude that the African LLACAN keyboard should be recommended in Niger because it covers all the characters used in the alphabets of the main Languages of this country, it produces valid Unicode codes and it minimizes the number of keys to be pressed.

    Free Register to Access Article