Before revision:  In this paper, we present a framework for emotions recognition and depression diagnosis from speechcalled EmoAudioNet. To preserve the high privacy of patient data, only speech is used. The deep EmoAudioNet studies the time-frequency representation of the audio signal and the visual representation of its spectrum of frequencies.
After revision:  In this paper, we present a new deep neural network architecture, called EmoAudioNet, for emotion and depression recognition from speech. Deep EmoAudioNet learns from the time-frequency representation of the audio signal and the visual representation of its spectrum of frequencies.