Carolin Kaiser

The usage of voice assistants is increasing steadily. Most recent available voice assistants talk with non-emotional tone. However, with technology becoming more humanoid, this is about to change. In human-human-interaction, people often catch the emotion of other people. With the increasing use of voice assistants, the question arises whether people also catch the expressed emotion of voice assistants. From a marketing perspective, this is especially interesting, as emotions play an important role while shopping. For example, happy customers tend to engage more in impulsive buying. Against this background, we explore how the tone of a voice assistant impacts consumers’ shopping attitude and behavior. In this talk, we present a new deep learning model to synthesize speech with different emotional tones (e.g. happy, uninvolved). Listening tests with experts, university students, and crowd workers prove that people can perceive the synthesized emotional tones. Afterward, we show the findings from a lab experiment, where we ask different groups of participants to test a voice shop with different emotional tones and we measure their emotion, shopping attitude, and shopping behavior. The results reveal, that the tone of the voice assistant in the shop impacts consumers’ emotional valence and arousal which in turn impact their trust in the shop, their satisfaction with the shop and the bought products and their impulsiveness of buying.