Automatic Power Emergency Dispatching System based on Voice Response

In recent years, there have been many blackouts in the world, which have a serious impact on social and economic development. Therefore, it has become an extremely important topic to study power emergency dispatching technology and reduce the loss caused by power emergency. In case of a large power accident, the data communication may be abnormal, and sensors may fail completely. At this time, dispatchers and field staff can only exchange accident information in the form of voice by telephones or mobile phones, and various instructions can only be issued in the form of voice. Even if we set up an automatic power emergency dispatching system, these voice messages and instructions can only be manually input while listening. It is slow in response and prone to errors, especially requiring a keyboard, which is inconvenient for field staff. For this reason, this paper presents to add a speech recognition module into the automatic power emergency dispatching system. At the same time, a semantic understanding module is trained by the knowledge base of the emergency decision system. Semantic understanding further improves the accuracy of speech recognition. The text after speech recognition is sorted into a standard format and input into a emergency decision-making system to get more accurate results, which are sent to field staff by voice.