Speech emotion recognition using deep learning

Speech emotion recognition, in short, as the SER and is an attempt to distinguish themselves from the human emotions and the emotional states of the human language. It is based on the fact that the vote reflects the often hidden emotions by tone of voice and pitch. This phenomenon can also be observed in animals, such as dogs and horses, so that they are able to understand human emotions. This can be difficult because there are not to be shared, and the description of the sound, this is a difficult task. It is the best example of a voice-recognition, emotions, and can be seen in the case of a call center. Communication is the best way of expressing your thoughts, ideas, and feelings. Among all the types of communication technologies, a audio, or a speech, it is the preferred, advanced, and professional means of communication between people. In the era of the Internet of Things is growing, and evolving, with more and more intelligent systems that will be available for day to day use. These types of applications, ranging from simple handheld devices, the structures of a complex of autonomous vehicles and automated systems that are used in various fields. Smart apps are more interactive and requires less effort on the part of the user experience, as well as the tendency to operate on the basis of the speech or voice control. This leads to the need for the computer to applications in order to fully understand human speech. The word in the image to find details on the conference, including gender, age, voice, and emotions, and on the pitch. A number of existing speech recognition systems that are used in IoT applications, which is integrated with a speech emotion recognition system for the analysis of one's emotional state.