Particular sound source detection method and particular sound source detection system based on deep neural network

The invention relates to a particular sound source detection method and a particular sound source detection system based on a deep neural network. The method comprises the following steps: extracting the acoustic features of a real-time sound signal to generate an acoustic feature vector; using a deep neural network method to train a preset sound signal, and building a DNN training model; and using the DNN training model to detect and judge the acoustic feature vector, and modeling different sound source signals by use of a deep neural network technology. As the deep neural network has more precise modeling ability and is of higher modeling accuracy especially under the premise of full data, sound sources with very approximate feature spaces can be detected. By using an adjacent time frame fusion feature technology, high single-frame detection accuracy is achieved, real-time performance is high, the judgment delay is not greater than 0.5 seconds, and practicability is high. 本发明种基于深度神经网络的特定声源检测方法与系统，其方法包括，提取实时