adaptNMT: an open-source, language-agnostic development environment for neural machine translation.
adaptNMT streamlines all processes involved in the development and deployment of RNN and Transformer neural translation models. As an open-source application, it is designed for both technical and non-technical users who work in the field of machine translation. Built upon the widely-adopted OpenNMT...
| Publicado en: | Language Resources & Evaluation Vol. 57; no. 4; pp. 1671 - 1697 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Springer Nature
Dec2023
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=173723398&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 173723398 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Dec2023 vid: 57 iid: 4 pid: 237 pub: Springer Nature artinfo: ui: 173723398 10.1007/s10579-023-09671-2 ppf: 1671 ppct: 26 formats: fmt: – @attributes: type: T – @attributes: type: P size: 1.7MB tig: atl: adaptNMT: an open-source, language-agnostic development environment for neural machine translation. aug: au: Lankford, Séamus Afli, Haithem Way, Andy affil: https://ror.org/04a1a1e81 ADAPT Centre, Dublin City University, Dublin, Ireland https://ror.org/013xpqh61 ADAPT Centre, Munster Technological University, Cork, Ireland su: Machine translating Neural development Natural language processing Environmental reporting User interfaces sug: subj: Machine translating Neural development Natural language processing Environmental reporting User interfaces keyword: Green NLP Language technology Neural machine translation NMT ab: adaptNMT streamlines all processes involved in the development and deployment of RNN and Transformer neural translation models. As an open-source application, it is designed for both technical and non-technical users who work in the field of machine translation. Built upon the widely-adopted OpenNMT ecosystem, the application is particularly useful for new entrants to the field since the setup of the development environment and creation of train, validation and test splits is greatly simplified. Graphing, embedded within the application, illustrates the progress of model training, and SentencePiece is used for creating subword segmentation models. Hyperparameter customization is facilitated through an intuitive user interface, and a single-click model development approach has been implemented. Models developed by adaptNMT can be evaluated using a range of metrics, and deployed as a translation service within the application. To support eco-friendly research in the NLP space, a green report also flags the power consumption and kgCO 2 emissions generated during model development. The application is freely available (http://github.com/adaptNMT). pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Language Resources & Evaluation is a copyright of Springer, 2023. All Rights Reserved. item: Language Resources & Evaluation holder: Springer Nature dt: @attributes: year: 2023 holdings: @attributes: islocal: N |
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