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.

最近的年度数据表明，语言服务是一个460亿美元的行业，并具有高增长预测。技术对于应对该领域的需求至关重要。在许多情况下，转换器现在编辑并与机器翻译（即类似于Google Translate的系统）进行编辑和交互，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，但是该过程颇具争议性，远非平稳。语言专业人士之间对机器翻译的态度是负面的。在媒体中，据说翻译人员是“拥有蓝调”（《经济学人》 2017年），并“关注”（El Pais 2017）关于机器翻译对他们的工作和工作的影响。培训翻译人员使用技术的方法通常是无效的，并且了解机器翻译如何影响翻译人员的语言决策仍然是有限的，这构成了在专业工作流程中对机器翻译的有益利用的障碍。该项目是解决这些问题并改善与翻译人员与技术互动相关的产品和流程的共同努力。我们将研究不同工作方法的功效，并评估可以在翻译工作场所部署的新培训方法。在有关自动化对人类劳动的影响的激烈辩论中，我们的目标最终是授权翻译人员以更有效和有益的方式采用机器翻译，以提高其工作满意度，提高专业标准并提高多语言经济。该项目将具有三个阶段。在第一阶段，我们将研究神经机器翻译的使用，机器翻译技术中的新范式，并评估翻译人员可以采用的不同策略来改善其工作。第二阶段将更深入地研究翻译行为与翻译文本质量之间的联系。迄今为止，我们将在最大规模的研究中研究这些链接，以建立翻译人员的工作与其产生的文本质量之间的联系。在研究方法和业务实践的创新整合中，该项目的第三阶段将研究如何在工作场所进行积极和负责任的方式跟踪翻译人员活动的工具（例如编辑和翻译速度）。我们将在四个月内监视翻译人员的活动，以阐明诸如数据伦理和对生产力的看法以及将项目初始阶段的方法纳入商业环境的实际含义。我们将使用该项目，我们将使用包括客观和主观技术在内的方法组合。这项工作在几种方面都是新颖的。首先，它将提供有关在商业环境中使用活动跟踪以及迄今为止通过行业标准和准则忽略的关键编辑程序的最佳实践文档。其次，该项目与多元化的研究人员和行业合作伙伴团队构成了翻译，学者，技术开发人员，翻译业务和专业机构之间的罕见合作。我们的工作源于与我们的专业合作伙伴报告并直接讨论的问题。最后，我们将偏离以前的举措，主要集中在开发新工具上，以代表对知识和能力建设的急需投资。迄今为止，翻译人员对该行业的担忧并不一定与经常无视技术使用者的技术上自上而下的投资保持一致，对技术开发人员和翻译人员的专业地位带来了潜在的负面影响。我们希望通过专注于技术进步的人类方面，并就新的工作方式和不同专业实践的疗效提供经验证据来改变这一点。