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VEHICLE AMBIENT AUDIO CLASSIFICATION VIA NEURAL NETWORK MACHINE LEARNING.

机译:通过神经网络机器学习对车辆进行音频分类。

摘要

A method and an apparatus for detecting and classifying sounds around a vehicle via neural network machine learning are described. The method involves an audio recognition system that may determine the origin of the sounds being inside or outside of a vehicle and classify the sounds into different categories such as adult, child, or animal sounds. The audio recognition system may communicate with a plurality of sensors in and around the vehicle to obtain information of conditions of the vehicle. Based on information of the sounds and conditions of the vehicles, the audio recognition system may determine whether an occupant or the vehicle is at risk and send alert messages or issue warning signals.
机译:描述了一种用于通过神经网络机器学习对车辆周围的声音进行检测和分类的方法和设备。该方法涉及音频识别系统,该音频识别系统可以确定在车辆内部或外部的声音的来源,并将声音分类为不同的类别,例如成人,儿童或动物的声音。音频识别系统可以与车辆内部和周围的多个传感器通信以获得车辆状况的信息。基于车辆的声音和状况的信息,音频识别系统可以确定乘员或车辆是否处于危险中并发送警报消息或发出警报信号。

著录项

  • 公开/公告号MX2017013379A

    专利类型

  • 公开/公告日2018-09-27

    原文格式PDF

  • 申请/专利权人 FORD GLOBAL TECHNOLOGIES LLC;

    申请/专利号MX20170013379

  • 发明设计人 ETHAN GROSS;

    申请日2017-10-17

  • 分类号G10L15/01;

  • 国家 MX

  • 入库时间 2022-08-21 12:51:13

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