Disrupter or enabler? Assessing the impact of using automatic speech recognition technology in interpreter-mediated legal proceedings

颠覆者还是推动者？

• 批准号: 2889440
• 金额: --
• 依托单位: University of Surrey
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2889440
• 关键词: Disrupter; enabler; Assessing; impact; using

Covid-19 has accelerated the use of communication technologies. In multilingual settings, this has increased the use of remote interpreting, whereby interpreters are connected to clients via digital platforms. Whilst remote interpreting is challenging, digital platforms create new opportunities to assist interpreters with their task. Automatic speech recognition (ASR) has been proposed as a state-of-the-art-technology that might support and indeed revolutionise the practice of interpreters. ASR can provide interpreters with a live transcript of the speech they are listening to and interpreting. This could have substantial benefits for interpreters in the legal setting. This is because legal proceedings now often require remote interpreting while communications in court and similar settings can be highly unpredictable, posing challenges for legal interpreters often lacking in training and preparation time. When working remotely, interpreters may face additional problems, such as poor sound quality. However, the research on remote legal interpreting has not yet investigated the use of ASR. To address this gap in the existing research, this study aims to assess the impact of ASR on interpreters' performance in remote legal interpreting. The specific objectives are: firstly, to develop a quality assessment model for remote legal interpreting that is sensitive to ASR use; secondly, to explore to what extent ASR can improve the performance of remote legal interpreters; thirdly, to investigate how interpreters adapt to this new technology. To this end, a two-stage methodology has been designed. Firstly, a comprehensive literature review will be conducted to adapt existing quality assessment approaches to evaluate interpreters' performance in remote legal interpreting, with and without ASR support. Secondly, empirical data will be collected through multiple resources, including simulated court hearings and reflective sessions with interpreters. Quantitative and qualitative data gathered through these resources will be cross-analysed to draw conclusions regarding the second and third objectives.

新型冠状病毒加快了通信技术的使用。在多语种环境中，这增加了远程口译的使用，口译员通过数字平台与客户联系。虽然远程口译具有挑战性，但数字平台为协助口译员完成任务创造了新的机会。自动语音识别（ASR）已被提出作为一个国家的最先进的技术，可能会支持，并确实彻底改变口译员的做法。ASR可以为口译员提供他们正在聆听和口译的演讲的现场记录。这对法律的环境中的口译员有很大好处。这是因为，法律的诉讼程序现在往往需要远距离口译，而法庭和类似场合的沟通可能非常不可预测，这对往往缺乏培训和准备时间的法律的口译员构成了挑战。在远程工作时，口译员可能面临其他问题，如音质差。然而，目前对远程法律的口译的研究还没有涉及到ASR的使用。为了弥补现有研究中的这一差距，本研究旨在评估自动语音识别对口译员远程法律的口译表现的影响。具体目标是：首先，建立一个对自动语音识别敏感的远程法律的口译质量评估模型; 2其次，探讨自动语音识别在多大程度上可以提高远程法律的口译员的口译水平; 3再次，调查口译员如何适应这种新技术。为此，设计了一个两阶段的方法。首先，本文将对现有的口译质量评估方法进行全面的文献综述，以评估口译员在远程法律的口译中的表现。其次，将通过多种资源收集经验数据，包括模拟法庭听证会和与口译员的反思会议。将对通过这些资源收集的定量和定性数据进行交叉分析，以得出关于第二和第三个目标的结论。