论文标题
音频海豚通信的汽车编码器
An Auto Encoder For Audio Dolphin Communication
论文作者
论文摘要
海豚交流和认知的研究需要详细检查可听见的海豚信号。这些信号的手动分析很麻烦且耗时。我们试图使用现代深度学习方法自动化分析的一部分。我们建议学习一种自动编码器，该自动编码器是根据以无监督方式训练的卷积和经常性层的。最终的模型将模式嵌入了可听见的海豚通信中。在几个实验中，我们表明嵌入可以用于聚类以及信号检测和信号类型分类。
Research in dolphin communication and cognition requires detailed inspection of audible dolphin signals. The manual analysis of these signals is cumbersome and time-consuming. We seek to automate parts of the analysis using modern deep learning methods. We propose to learn an autoencoder constructed from convolutional and recurrent layers trained in an unsupervised fashion. The resulting model embeds patterns in audible dolphin communication. In several experiments, we show that the embeddings can be used for clustering as well as signal detection and signal type classification.
