This new corpus, called EMOLY (EMOtion and AnomaLY), is composed of speech and facial video records of subjects that contain controlled anomalies. As far as we know, to study the problem of anomaly detection in discourse by using machine learning classification techniques, no such corpus exists or is available to the community. In EMOLY, each subject is recorded three times in a recording studio, by filming his/her face and recording his/her voice with a HiFi microphone. The corpus is recorded in French language. Anomalies in discourse are induced or acted. At this time, about 3.7 hours of usable audiovisual recording on which we have tested classical classification techniques (GMM or One Class-SVM plus threshold classifier) are available. Results confirm the usability of the anomaly induction mechanism to produce anomalies in discourse and also the usability of the corpus to improve detection techniques. Our final aim is then to increase the volume of the corpus in a second phase, with new subjects and some variation on the anomaly place and type.

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