In this article, we describe experiments on the detection of three emotional states (Anger, Positive and Neutral) for two French corpora collected in call centers in different contexts (service complaints and medical emergency). These corpora have a high level of privacy. In order to be comparable with results obtained in the community we used the openEAR acoustic features extraction platform instead of our own library. One of our aims being the comparison of anger and positive emotions across corpora, we train models on one corpus and test it on the other to compare their similarities, then conversely. We will discuss the possible gain in generalization power.