论文标题
使用长期记忆的呼吸道声音分类
Respiratory Sound Classification Using Long-Short Term Memory
论文作者
论文摘要
开发可靠的声音检测和识别系统可提供许多好处，并在不同行业中拥有许多有用的应用。本文研究了试图执行与呼吸系统疾病分类有关的声音分类时存在的困难。检查了一些已采用的方法，例如独立的组件分析和盲源分离。最后，进行了有关使用深度学习和长期短期内存网络的检查，以确定如何实现此类任务。
Developing a reliable sound detection and recognition system offers many benefits and has many useful applications in different industries. This paper examines the difficulties that exist when attempting to perform sound classification as it relates to respiratory disease classification. Some methods which have been employed such as independent component analysis and blind source separation are examined. Finally, an examination on the use of deep learning and long short-term memory networks is performed in order to identify how such a task can be implemented.
