权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Improving Products and Processes in Translation Technology Use (IMPETUS)

改进翻译技术使用的产品和流程 (IMPETUS)

基本信息

批准号：
ES/S014446/1
负责人：
Lucas Nunes Vieira
金额：
$ 30.64万
依托单位：
University of Bristol
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2019
资助国家：
英国
起止时间：
2019 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=ES%2FS014446%2F1
关键词：
Improving Products Processes Translation Technology

项目摘要

Recent annual figures show that language services are a US$46-billion industry with high growth forecasts. Technology is crucial for coping with demand in this sector. In many contexts, translators now edit and interact with machine translation (i.e. systems akin to Google Translate) instead of translating texts from scratch. The productivity benefits of using machine translation in this way are well known, but the process is controversial and far from smooth. Attitudes to machine translation among language professionals are famously negative. In the press, translators are said to 'have the blues' (The Economist 2017) and to be 'concerned' (El Pais 2017) about the impact of machine translation on their jobs and work. Methods for training translators to use technology are often ineffective, and knowledge of how machine translation affects translators' linguistic decisions is still limited, which poses obstacles to a beneficial use of machine translation in professional workflows. This project is a joint effort to address these issues and improve products and processes linked to translators' interaction with technology. We will examine the efficacy of different working methods and assess new training approaches that can be deployed in the translation workplace. In a context of heated debates on the impact of automation on human labour, our aim is ultimately to empower translators to adopt machine translation in more effective and rewarding ways that can improve their job satisfaction, raise professional standards and boost the multilingual economy.The project will have three phases. In the first phase, we will investigate the use of neural machine translation, a new paradigm in machine translation technology, and assess different strategies that translators can adopt to improve their work. The second phase will delve deeper into links between translating behaviour and the quality of translated texts. We will examine these links across languages in the largest-scale study to date to establish a connection between what translators do and the quality of the texts they produce. In an innovative integration of research methods and business practices, the third phase of the project will examine how tools that track translators' activity (e.g. edits and translating speed) can be used positively and responsibly in the workplace. We will monitor translators' activity for four months to shed new light on issues such as data ethics and perceptions of productivity as well as on the practical implications of incorporating methods from the project's initial phases into commercial contexts.Throughout the project, we will use a unique combination of methodologies including objective and subjective techniques. The work is novel in several ways. First, it will provide best-practice documentation on the use of activity tracking in commercial settings and on key editing procedures so far ignored by industry standards and guidelines. Second, with a diverse team of researchers and industry partners, the project constitutes a rare collaboration between translators, academics, technology developers, translation businesses and professional bodies. Our work is rooted in problems reported by and discussed directly with our professional partners. Finally, we will veer away from previous initiatives focused predominantly on the development of new tools to represent a much-needed investment in know-how and capacity building. To date, translators' concerns about the profession have not necessarily aligned with top-down investments in technology that often disregard the technology users, with potentially negative consequences for the technology developers and for translators' professional standing. We hope to change this by concentrating on the human aspects of technological progress and providing empirical evidence on new ways of working and the efficacy of different professional practices.

最近的年度数据显示，语言服务是一个价值460亿美元的行业，预计将实现高增长。技术对于满足这一部门的需求至关重要。在许多情况下，翻译人员现在编辑并与机器翻译（即类似于Google翻译的系统）交互，而不是从头开始翻译文本。以这种方式使用机器翻译的生产力优势是众所周知的，但这个过程是有争议的，而且远非顺利。语言专业人士对机器翻译的态度是出了名的消极。在媒体上，翻译人员被称为“忧郁”（The Economist 2017），并“担心”（El Pais 2017）机器翻译对其工作和工作的影响。培训翻译人员使用技术的方法往往是无效的，机器翻译如何影响翻译人员的语言决策的知识仍然有限，这对在专业工作流程中有效使用机器翻译构成了障碍。该项目旨在解决这些问题，并改进与翻译人员与技术互动相关的产品和流程。我们将研究不同工作方法的有效性，并评估可在翻译工作场所部署的新培训方法。在关于自动化对人类劳动力影响的激烈辩论的背景下，我们的目标是最终使翻译人员能够以更有效和更有益的方式采用机器翻译，从而提高他们的工作满意度，提高专业水平并促进多语言经济。在第一阶段，我们将研究神经机器翻译的使用，这是机器翻译技术中的一种新范式，并评估翻译人员可以采取的不同策略来改进他们的工作。第二阶段将深入研究翻译行为与译文质量之间的联系。我们将在迄今为止最大规模的研究中研究这些跨语言的联系，以建立译者的工作与他们所产生的文本质量之间的联系。该项目第三阶段将创新性地整合研究方法和业务做法，研究如何在工作场所积极和负责任地使用跟踪笔译员活动的工具（例如编辑和翻译速度）。我们将对翻译人员的活动进行为期四个月的监控，以揭示数据伦理和生产力观念等问题，以及将项目初始阶段的方法融入商业环境的实际影响。在整个项目中，我们将使用独特的方法组合，包括客观和主观技术。这部作品在几个方面都很新颖。首先，它将提供关于在商业环境中使用活动跟踪的最佳做法文件，以及关于迄今被行业标准和准则忽视的关键编辑程序的最佳做法文件。其次，该项目拥有多元化的研究人员和行业合作伙伴团队，是翻译人员、学者、技术开发人员、翻译企业和专业机构之间的罕见合作。我们的工作植根于我们的专业合作伙伴报告并直接与他们讨论的问题。最后，我们将改变以往主要侧重于开发新工具的举措，以代表对专门知识和能力建设的迫切需要的投资。迄今为止，翻译人员对翻译职业的关注并不一定与自上而下的技术投资相一致，这种投资往往忽视技术用户，对技术开发人员和翻译人员的专业地位可能产生负面影响。我们希望通过专注于技术进步的人的方面，并提供新的工作方式和不同专业实践的有效性的经验证据来改变这一点。