Abstract: 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.

Key words: vocal communication, common raven calls, artificial intelligence, back propagation neural network, neural states

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。

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