In this paper, we propose an algorithm, Epochal Difficult Captions, to supplement the training of any model for the Automated Audio Captioning task. Epochal Difficult Captions is an elegant evolution to the keyword estimation task that previous work have used to train the encoder of the AAC model. Epochal Difficult Captions modifies the target captions based on a curriculum and a difficulty level determined as a function of current epoch. Epochal Difficult Captions can be used with any model architecture and is a lightweight function that does not increase training time. We test our results on three systems and show that using Epochal Difficult Captions consistently improves performance
翻译:在本文中,我们提出一种算法,即 " Epochal difficult Captions ",以补充自动声控任务任何模型的培训。 " Epochal difficult Captions " 是以往用于培训 AAC 模型编码器的关键词估计任务的一个优雅的演变。 " Epochal difficult Captions " 根据课程和按当前时代函数确定的难度水平修改目标标题。 " 任何模型结构都可以使用 " opochal difficult Captions ",这是一个轻量功能,不会增加培训时间。我们在三个系统中测试我们的结果,并表明使用 " Epochal Captions " 不断改进绩效。