EmoMatchSpanishDB

These are the two datasets features used and described in the research paper entitled "EmoMatchSpanishDB: Study of Machine Learning Models in a New Spanish Elicited Dataset".<br>In this paper we address the task of real time emotion recognition for elicited emotions. For this purpose we have created a publicly accessible dataset composed by fifty subjects expressing the emotions of anger, disgust, fear, happiness, sadness, and surprise in Spanish language. In addition, a neutral tone of each subject has been added. This article describes how this database have been created including the recording and the performed crowdsourcing perception test in order to statistically validate the emotionof each sample and remove noisy data samples. Moreover we present a baseline comparative study between different machine learning techniques in terms of accuracy, specificity, precision, and recall. Prosodic and spectral features are extracted and used for this classification purpose. We expect that this database will be useful to get new insights within this area of study.<br>The first dataset is "EmoSpanishDB" that contains a set of 13 and 140 spectral and prosodic features for a total of 3550 audios of 50 individuals reproducing the 12 sentences for the six different emotions, ’anger, disgust, fear, happiness, sadness, surprise’ (Ekman’s basic emotions]) plus neutral.<br>The second dataset is "EmoMatchSpanishDB" and contains a set of 13 and 140 spectral and prosodic features for a total of 2050 audios of 50 individuals reproducing the 12 sentences for the six different emotions, ’anger, disgust, fear, happiness, sadness, surprise’ (Ekman’s basic emotions]) plus neutral. These 2050 audios' features are a subset of EmoSpanishDB resulting of the matched audios after application of a crowdsourcing process to validate that the elicited emotion corresponds with the expressed.<br><br>These datasets have been used in the paper "EmoMatchSpanishDB: Study of Machine Learning Models in a New Spanish Elicited Dataset" and their creation, its contents, and also a set of baseline machine learning experiments and results are fully described within it.<br>The features are available under MIT license and if you want to get access to the original raw audio files for creating your own features and research purposes you can get them under CC-BY-NC completing and signing the agreement file (EMOMATCHAgreement.docx) and sending it via email to [e-mail]