First Progresses in Evaluation of Resonance in Staff Selection through Speech Emotion Recognition

Speech Emotion Recognition (SER) is a hot research topic in the field of Human Computer Interaction. In this paper a SER system is developed with the aim of providing a classification of the “state of interest” of a human subject involved in a job interview. Classification of emotions is performed by analyzing the speech produced during the interview. The presented methods and results show just preliminary conclusions, as the work is part of a larger project including also analysis, investigation and classification of facial expressions and body gestures during human interaction. At the current state of the work, investigation is carried out by using software tools already available for free on the web; furthermore, the features extracted from the audio tracks are analyzed by studying their sensitivity to an audio compression stage. The Berlin Database of Emotional Speech (EmoDB) is exploited to provide the preliminary results.