With the growth of interpreting technologies, from remote interpreting and Computer-Aided Interpreting to automated speech translation and interpreting avatars, there is now a high demand for ways to quickly and efficiently measure the quality of any interpreting delivered. A range of approaches to fulfil the need for quick and efficient quality measurement have been proposed, each involving some measure of automation. This article examines these recently-proposed quality measurement methods and will discuss their suitability for measuring the quality of authentic interpreting practice, whether delivered by humans or machines, concluding that automatic metrics as currently proposed cannot take into account the communicative context and thus are not viable measures of the quality of any interpreting provision when used on their own. Across all attempts to measure or even categorise quality in Interpreting Studies, the contexts in which interpreting takes place have become fundamental to the final analysis.

翻译：随着口译技术的发展，从远程口译、计算机辅助口译到自动语音翻译及口译虚拟形象，当前亟需能够快速高效衡量各类口译交付质量的方法。为满足快速高效的质量评估需求，一系列涉及某种自动化程度的测量方法被提出。本文检视了这些近期提出的质量测量方法，并讨论其对于衡量真实口译实践（无论是人工还是机器交付）质量的适用性，结论指出当前提出的自动指标无法考量交际语境，因此单独使用时不能作为任何口译服务质量的可行衡量标准。在口译研究中所有尝试测量甚至分类质量的努力中，口译发生的语境已成为最终分析的根本要素。