Research
Voice Analytics
Sounding Out Emotions
For several years now, the automatic analysis of emotions for market research purposes has been a primary research area for the GfK Verein. Working together with engineers at the University of Augsburg and start-up firm audEERING, the GfK Verein has developed an instrument that detects emotions using the voice.
Voice analysis is now available for GfK customers
For GfK clients, emotional voice analysis is available in GfK’s Market Builder Voice, which was awarded with the Innovation Prize of the German Market Research Association in 2017.
The NIM has already developed sophisticated software in this field. The facial coding automatically uses facial expressions to detect emotions. However, visual methods of emotion recognition are not always possible, such as in telephone interviews. Moreover, not all emotional states can be measured through facial expressions. For instance, emotional arousal cannot be inferred from facial expressions. Emotional arousal is an important indicator of the personal relevance of certain experiences and can be easily detected in the voice.
Voice Analytics – “Sounding Out the Consumer’s Voice”
In a mission to expand the range of applications for emotion analysis, the NIM collaborated with engineers at the University of Augsburg and the start-up firm audEERING to develop an instrument that would recognize emotions through vocal patterns. The current version of the software automatically detects emotional arousa in five languages: German, English, Spanish, Chinese, and Russian.
Cooperation partner
- audEERING GmbH
- Prof. Dr. Björn Schuller, Augsburg University, Imperial College London
Publications
- Eyben, F., Unfried, M., Hagerer, G., & Schuller, B. (2017). Automatic multi-lingual arousal detection from voice applied to real product testing applications. Proceedings of the 42nd IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP, New Orleans, LA, USA.
- Dieckmann, A., & Unfried, M. (2020). Thrilled or Upset: What Drives People to Share and Review Product Experiences? NIM Marketing Intelligence Review, 12(2), 56–61. DOI: https://doi.org/10.2478/nimmir-2020-0019
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