A Scoping Review on the Use of Voice Biomarkers for Emotional Assessment

Speech Emotion Recognition (SER) is an umbrella term that encompasses all Machine Learning & Deep Learning (ML/DL) algorithms used for the very specific task of extracting emotional state from human speech. In literature, various techniques have been utilized to extract emotions from signals, including well-established speech analysis and classification techniques. Using the scoping review method, the paper maps techniques for speech-based emotion recognition. In doing so, it presents elements defining the use of algorithms to assess emotions, for example, databases used for emotion recognition, notions and types of emotions considered, and empirical investigations made toward SER and related limitations. The contribution places particular emphasis on the existing perspectives and practices in order to offer a series of recommendations for future developments.