A large part of our daily lives is spent with audio information. Massive obstacles are frequently presented by the colossal amounts of acoustic information and the incredibly quick processing times. This results in th...A large part of our daily lives is spent with audio information. Massive obstacles are frequently presented by the colossal amounts of acoustic information and the incredibly quick processing times. This results in the need for applications and methodologies that are capable of automatically analyzing these contents. These technologies can be applied in automatic contentanalysis and emergency response systems. Breaks in manual communication usually occur in emergencies leading to accidents and equipment damage. The audio signal does a good job by sending a signal underground, which warrants action from an emergency management team at the surface. This paper, therefore, seeks to design and simulate an audio signal alerting and automatic control system using Unity Pro XL to substitute manual communication of emergencies and manual control of equipment. Sound data were trained using the neural network technique of machine learning. The metrics used are Fast Fourier transform magnitude, zero crossing rate, root mean square, and percentage error. Sounds were detected with an error of approximately 17%;thus, the system can detect sounds with an accuracy of 83%. With more data training, the system can detect sounds with minimal or no error. The paper, therefore, has critical policy implications about communication, safety, and health for underground mine.展开更多
本文阐述了使用"Cool Edit Pro 2.1"录音软件制作外语听力音频试题的应用实践,从而解决了没有专业录音室和专业录音设备的情况下,如何制作高质量的录音音频试题的困难,为大多数教师在制作录音音频试题时,提供了应用实践的方...本文阐述了使用"Cool Edit Pro 2.1"录音软件制作外语听力音频试题的应用实践,从而解决了没有专业录音室和专业录音设备的情况下,如何制作高质量的录音音频试题的困难,为大多数教师在制作录音音频试题时,提供了应用实践的方法、步骤、注意事项等.对使用普通录音机制作音频试题时出现的噪音的消除、试题的顺序调整、各题之间间隔调整等难以解决的问题,变得迎刃而解,十分容易.展开更多
文摘A large part of our daily lives is spent with audio information. Massive obstacles are frequently presented by the colossal amounts of acoustic information and the incredibly quick processing times. This results in the need for applications and methodologies that are capable of automatically analyzing these contents. These technologies can be applied in automatic contentanalysis and emergency response systems. Breaks in manual communication usually occur in emergencies leading to accidents and equipment damage. The audio signal does a good job by sending a signal underground, which warrants action from an emergency management team at the surface. This paper, therefore, seeks to design and simulate an audio signal alerting and automatic control system using Unity Pro XL to substitute manual communication of emergencies and manual control of equipment. Sound data were trained using the neural network technique of machine learning. The metrics used are Fast Fourier transform magnitude, zero crossing rate, root mean square, and percentage error. Sounds were detected with an error of approximately 17%;thus, the system can detect sounds with an accuracy of 83%. With more data training, the system can detect sounds with minimal or no error. The paper, therefore, has critical policy implications about communication, safety, and health for underground mine.
文摘本文阐述了使用"Cool Edit Pro 2.1"录音软件制作外语听力音频试题的应用实践,从而解决了没有专业录音室和专业录音设备的情况下,如何制作高质量的录音音频试题的困难,为大多数教师在制作录音音频试题时,提供了应用实践的方法、步骤、注意事项等.对使用普通录音机制作音频试题时出现的噪音的消除、试题的顺序调整、各题之间间隔调整等难以解决的问题,变得迎刃而解,十分容易.
