标题： 利用声音事件检测增强音频描述中的时间关系 显示英文标题

标题： Enhance Temporal Relations in Audio Captioning with Sound Event Detection

摘要： 自动化音频描述旨在为给定的音频片段生成自然语言描述，不仅检测和分类声音，还总结音频事件之间的关系。 音频描述领域的最新研究进展引入了额外的指导以提高生成句子中音频事件的准确性。 然而，在揭示复杂关系方面，音频事件之间的时间关系很少受到关注，而揭示复杂关系是总结音频内容的关键组成部分。 因此，本文旨在通过声音事件检测（SED），一项定位事件时间戳的任务，更好地捕捉描述生成中的时间关系。 我们研究了在描述模型中整合时间信息的最佳方法，并提出了一种时间标签系统，将时间戳转换为可理解的关系。 通过所提出的时空度量进行评估的结果表明，在时间关系生成方面取得了显著改进。 显示英文摘要

摘要： Automated audio captioning aims at generating natural language descriptions for given audio clips, not only detecting and classifying sounds, but also summarizing the relationships between audio events. Recent research advances in audio captioning have introduced additional guidance to improve the accuracy of audio events in generated sentences. However, temporal relations between audio events have received little attention while revealing complex relations is a key component in summarizing audio content. Therefore, this paper aims to better capture temporal relationships in caption generation with sound event detection (SED), a task that locates events' timestamps. We investigate the best approach to integrate temporal information in a captioning model and propose a temporal tag system to transform the timestamps into comprehensible relations. Results evaluated by the proposed temporal metrics suggest that great improvement is achieved in terms of temporal relation generation.