Building a translators community¶
Following these recommendations supports the creation of a full, multilingual post-editing tool. Good translations are defined through the systemic-functional model of House which aims at a contextual correct translation. Write your own post-editing guide and alter these recommendations to fit your own definitions. In most cases the browser-plugin of languageTool is useful as a proof-reading tool.
Muchas veces, los traductores encontrarán problemas con las cadenas de origen. Asegúrese de que les resulte fácil informar sobre dichos problemas. Para recopilar esta información, puede configurar el campo Explorador del repositorio en su componente Weblate, para que los traductores propongan sus cambios al repositorio original. También puede recibir comentarios de los traductores si configura Dirección para informar de errores en las cadenas de origen.
Lista de control de regionalización comunitaria¶
La Lista de comprobación de ubicación comunitaria que se encuentra en el menú de cada componente puede servirle de guía para facilitar el proceso de localización a los traductores comunitarios.
Terminology management¶
Post-editing of MT with terminology assignment influences each level of the translation process. The machine translation system can be adapted to the specific vocabulary and style with a continued training or neural fuzzy repair. Import your existing translation memory into weblate or create an initial scope with your basic terminology. In the end the lector should be instructed with additional terminology documents to guarantee a good knowledge and output in the field.
Traducción automática¶
La calidad de la traducción automática (que suele medirse con la puntuación BLEU) se correlaciona con el tiempo de edición [1]. Elija un backend automático que admita los idiomas y dominios necesarios. Deje en claro cómo funciona el backend de traducción y qué calidad debe esperar el poseditor.
Review translations¶
The translations should be reviewed by a second person after the post-editing. With an impartial and competent reviewer, the two people rule reduces the errors and improves the quality and consistency of the content. Providing reviewers with previews or alpha translations will make for the best review. Screenshots, explanations also help to review the strings in context.
Structured feedback¶
There are many Comprobaciones y correcciones in Weblate that provide structured feedback on the quality of the translations. They also give visual feedback during translation. This prevents recurring mistakes, and helps translators to understand how the code works.
Translation definition¶
In addition to the mentalistic and impact-based definitions which make a strong reduction, the text-based linguistic approach fits best with the implemented translation methods. A well-formulated theory for translation evaluation is House’s systemic-functional model, which focuses on the relation between original and translation. The model assumes that translation is an attempt to keep the semantic, pragmatic, and textual meaning of a text equivalent when crossing from one linguistic code to another.
The degree of quality of a translation is based on the degree of equivalence, the correspondence between the text profile and the text function. Because it cannot be calculated automatically, sufficient information should be collected to enable a uniform human evaluation. The two main parameters of agreement in a corresponding model are the macro-context – i.e. embedding in a larger social and literary context – and the micro-context consisting of field, tenor and mode.
Orígenes¶
Marina Sanchez-Torron and Philipp Koehn in Machine Translation Quality and Post-Editor Productivity, Figure 1: https://www.cs.jhu.edu/~phi/publications/machine-translation-quality.pdf
Joanna Best und Sylvia Kalina. Übersetzen und Dolmetschen: eine Orientierungshilfe. A. Francke Verlag Tübingen und Base, 2002. Möglichkeiten der Übersetzungskritik starting on page number 101
neural fuzzy repair, Bram Bulté and Arda Tezcan in Neural Fuzzy Repair: Integrating Fuzzy Matches into Neural Machine Translation, 2019 https://aclanthology.org/P19-1175.pdf