Fake Moods: Can Users Trick an Emotion-Aware VoiceBot?

BSTRACT The ability to deal properly with emotion could be a critical feature of future VoiceBots. Humans might even choose to use fake emotions, e.g., sound angry to emphasize what they are saying or sound nice to get what they want. However, it is unclear whether current emotion detection methods detect such acted emotions properly, or rather the true emotion of the speaker. We asked a small number of participants (26) to mimic five basic emotions and used an open source emotion-in-voice detector to provide feedback on whether their acted emotion was recognized as intended. We found that it was difficult for participants to mimic all five emotions and that certain emotions were easier to mimic than others. However, it remains unclear whether this is due to the fact that emotion was only acted or due to the insufficiency of the detection software. As an intended side effect, we collected a small corpus of labeled data for acted emotion in speech, which we plan to extend and eventually use as training data for our own emotion detection. We present the study setup and discuss some insights on our results.