We present a study of a neural network based method for speech emotion recognition, using audio-only features. In the studied scheme, the acoustic features are extracted from the audio utterances and fed to a neural network that consists of CNN layers, BLSTM combined with an attention mechanism layer, and a fully-connected layer. To illustrate and analyze the classification capabilities of the network we used the t-SNE method. We evaluated our model using RAVDESS and IEMOCAP databases.