We present a contribution to the Open Performance subchallenge of the INTERSPEECH 2009 Emotion Challenge. We evaluate the feature extraction and classifier of EmoVoice, our framework for real-time emotion recognition from voice on the challenge database and achieve competitive results. Furthermore, we explore the benefits of discretizing numeric acoustic features and find it beneficial in a multi-class task.