摘要
目的通过声音交流区分生物体的神经或精神状态。方法本研究采用人工网络方法(反向传播神经网络),对渡鸦(Corvus corax)鸣叫背后的神经生物学意义进行分类。结果渡鸦鸣叫分为四种:警报、飞行、乞求和歌唱。人工智能分类,可帮助我们通过动物发声情况,区分动物的精神状态。结论反向传播神经网络,是一种很有前途的渡鸦鸣叫分类的候选方法。
Objective The neural or mental states of an organism are distinguished by vocal communication.Method This research used artificial network method(back propagation neural network) to classify the neurobiological meaning behind the calls of the common raven(Corvus corax).Result There were four types of common raven calls,including alarming,flighting,begging and singing.Artificial intelligence classification can help us distinguish the neural state of animals through the calls of animals.Conclusion Back propagation neural network is a promising candidate method for classification of raven calls.
作者
杨利琼
徐帆
刘昉昉
YANG Liqiong;XU Fan;LIU Fangfang(Department of Pharmacy,Chengdu Medical College,Chengdu 610500,China;Department of Public Health,Chengdu Medical College,Chengdu 610500,China;Southwest Minzu University,Chengdu 610041,China)
出处
《实验动物科学》
2022年第6期45-51,共7页
Laboratory Animal Science
基金
西南民族大学中央高校基本科研业务费专项资金资助(2021NYB08)
成都医学院自然科学基金(CYZ18-33)。
关键词
声音交流
渡鸦鸣叫
人工智能
反向传播神经网络
神经状态
vocal communication
common raven calls
artificial intelligence
back propagation neural network
neural states