从文本到口头交流：将情感分析应用于软件项目会议
From Textual to Verbal Communication: Towards Applying Sentiment Analysis to a Software Project Meeting
摘要：
情感分析在软件工程中得到越来越多的关注，研究人员提供了新的见解和新的工具。现有的用例和工具旨在用于文本通信，例如对协作版本控制系统的评论。虽然这已经可以为开发团队提供有用的反馈，但大量的交流发生在会议上，不适合当前的工具设计和概念。在本文中，我们提出了一个概念，能够处理现场会议音频和分类转录语句到情感极性类。我们结合了开源语音识别的最新进展和以前在情感分析方面的研究。我们在一个学生软件项目会议上测试了我们的方法，以获得概念证明，在我们的工具和会议音频上的人类观察员之间显示出适度的一致性。尽管我们的研究的初步性质，我们看到有前途的结果，激励未来的研究在情感分析会议。例如，极性分类可以扩展到检测可能危及项目成功的破坏性行为。
英文摘要：
Sentiment analysis gets increasing attention in software engineering with new tools emerging from new insights provided by researchers. Existing use cases and tools are meant to be used for textual communication such as comments on collaborative version control systems. While this can already provide useful feedback for development teams, a lot of communication takes place in meetings and is not suited for present tool designs and concepts. In this paper, we present a concept that is capable of processing live meeting audio and classifying transcribed statements into sentiment polarity classes. We combine the latest advances in open source speech recognition with previous research in sentiment analysis. We tested our approach on a student software project meeting to gain proof of concept, showing moderate agreement between the classifications of our tool and a human observer on the meeting audio. Despite the preliminary character of our study, we see promising results motivating future research in sentiment analysis on meetings. For example, the polarity classification can be extended to detect destructive behaviour that can endanger project success.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
