Deep Learning algorithms are often used as black box type learning and they are too complex to understand. The widespread usability of Deep Learning algorithms to solve various machine learning problems demands deep and transparent understanding of the internal representation as well as decision making. Moreover, the learning models, trained on sequential data, such as audio and video data, have intricate internal reasoning process due to their complex distribution of features. Thus, a visual simulator might be helpful to trace the internal decision making mechanisms in response to adversarial input data, and it would help to debug and design appropriate deep learning models. However, interpreting the internal reasoning of deep learning model is not well studied in the literature. In this work, we have developed a visual interactive web application, namely d-DeVIS, which helps to visualize the internal reasoning of the learning model which is trained on the audio data. The proposed system allows to perceive the behavior as well as to debug the model by interactively generating adversarial audio data point. The web application of d-DeVIS is available at ddevis.herokuapp.com.
翻译:深学习算法往往被用作黑盒式学习,而且过于复杂,难以理解。深学习算法的广泛使用对于解决各种机器学习问题来说,要求深入和透明地理解内部代表和决策。此外,由于功能分布复杂,在连续数据(如音频和视频数据)方面受过训练的学习模型具有复杂的内部推理程序。因此,视觉模拟器可能有助于跟踪内部决策机制,以回应对立输入数据,有助于调试和设计适当的深学习模型。然而,深学习模型的内部推理在文献中研究得并不完善。在这项工作中,我们开发了一个视觉互动的网络应用程序,即 d-DeVIS,它有助于将接受音频数据培训的学习模型的内部推理进行视觉化。拟议的系统能够通过互动生成对立音频数据点来了解行为和调试模型。 d-DeVIS 的网络应用程序可在 dedevis.herokapp.com上查阅。