Communication for processing relevant information plays a paramount role in developing a comprehensive understanding of Search and Rescue (SAR) situations and conducting operations in a successful and reliable manner. Nevertheless, communication systems have not changed 20considerably in the context of simplifying very high frequency (VHF) maritime communication and enhancing the value of SAR practices. The Automated Transcription of Maritime VHF Radio Communication for SAR Mission Coordination (ARTUS) project approaches this problem with the development of an assistance system which employs AI-based speech recognition and smart direction finding. First, ideas and specified needs of end users for designing the user interface are presented in this paper. Further, preliminary accomplishments of domain specific language training for maritime speech recognition, and the direction-finding algorithms for localizing senders are sketched out. While the preliminary results build a solid ground, additional field experiments will be conducted in order to enhance the accuracy and reliability of speech recognition and direction finding. The identified end user requirements across different personnel groups show commonalities, but call for a differentiated approach in order to meet the challenges and peculiar needs of the various working contexts.

中文翻译：

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借助基于AI的语音识别和智能方向查找功能，协助海上搜索与救援（SAR）人员

处理相关信息的通信在全面理解搜索和救援（SAR）情况以及以成功和可靠的方式进行操作方面起着至关重要的作用。但是，在简化甚高频（VHF）海事通信和提高SAR实践的价值的背景下，通信系统的变化还没有发生20倍的变化。用于SAR任务协调的海上VHF无线电通信自动转录（ARTUS）项目通过使用基于AI的语音识别和智能测向的辅助系统的开发来解决此问题。首先，本文提出了最终用户设计用户界面的想法和特定需求。进一步，勾勒出了海上语音识别领域专用语言训练的初步成果，以及定位发送方的方向寻找算法。在初步结果奠定坚实基础的同时，将进行其他野外实验，以提高语音识别和测向的准确性和可靠性。已确定的跨不同人员组的最终用户需求具有共同点，但需要一种差异化的方法来满足各种工作环境的挑战和特殊需求。为了提高语音识别和测向的准确性和可靠性，还将进行其他野外实验。已确定的跨不同人员组的最终用户需求具有共同点，但需要一种差异化的方法来满足各种工作环境的挑战和特殊需求。为了提高语音识别和测向的准确性和可靠性，还将进行其他野外实验。已确定的跨不同人员组的最终用户需求具有共同点，但需要一种差异化的方法来满足各种工作环境的挑战和特殊需求。