In human-computer interaction, particularly in multimedia delivery, information is communicated to users sequentially, whereas users are capable of receiving information from multiple sources concurrently. This mismatch indicates that a sequential mode of communication does not utilise human perception capabilities as efficiently as possible. This article reports an experiment that investigated various speech-based (audio) concurrent designs and evaluated the comprehension depth of information by comparing comprehension performance across several different formats of questions (main/detailed, implied/stated). The results showed that users, besides answering the main questions, were also successful in answering the implied questions, as well as the questions that required detailed information, and that the pattern of comprehension depth remained similar to that seen to a baseline condition, where only one speech source was presented. However, the participants answered more questions correctly that were drawn from the main information, and performance remained low where the questions were drawn from detailed information. The results are encouraging to explore the concurrent methods further for communicating multiple information streams efficiently in human-computer interaction, including multimedia.

中文翻译：

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基于并发语音的设计中的信息理解评估

在人机交互中，特别是在多媒体传递中，信息是按顺序传递给用户的，而用户能够同时从多个来源接收信息。这种不匹配表明顺序通信模式没有尽可能有效地利用人类感知能力。本文报告了一项实验，该实验调查了各种基于语音（音频）的并发设计，并通过比较几种不同形式的问题（主要/详细、暗示/陈述）的理解性能来评估信息的理解深度。结果表明，用户除了回答主要问题外，还成功回答了隐含问题以及需要详细信息的问题，并且理解深度的模式与只呈现一个语音源的基线条件相似。然而，参与者正确回答了更多从主要信息中提取的问题，并且在从详细信息中提取问题的情况下，表现仍然很低。结果令人鼓舞，进一步探索在人机交互（包括多媒体）中有效地传递多个信息流的并发方法。