{Kai Yu Mengyue Wu Zeyu Xie Xuenan Xu}

Abstract

This report proposes an audio captioning system for the Detectionand Classification of Acoustic Scenes and Events (DCASE) 2021challenge task Task 6. Our audio captioning system consists of a10-layer convolution neural network (CNN) encoder and a tempo-ral attentional single layer gated recurrent unit (GRU) decoder. Inthis challenge, there is no restriction on the usage of external dataand pre-trained models. To better model the concepts in an audioclip, we pre-train the CNN encoder with audio tagging on AudioSet.After standard cross entropy based training, we further fine-tune themodel with reinforcement learning to directly optimize the evalua-tion metric. Experiments show that our proposed system achieves aSPIDEr of 28.6 on the public evaluation split without ensemble1.