Real-time emotion recognition for sales

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference article in proceedingsScientificvertaisarvioitu

7 Sitaatiot (Scopus)
214 Lataukset (Pure)


Positive emotion is a pre-condition to any sales contract. Likewise, the ability to perceive the emotions of a customer impacts sales performance.To support emotional perception in buyer-seller interactions, we propose an audio-visual emotion recognition system that can recognize eight emotions: neutral, calm, sad, happy, angry, fearful, surprised, and disgusted. We reduced noise in audio samples and we applied transfer learning for image feature extraction based on a pre-trained deep neural network VGG16. For emotion recognition, we successfully obtained an audio emotion-recognition accuracy of 62.51% and 68% and video emotion-recognition accuracy of 97.13% and 97.77% on the Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) and Surrey Audio-Visual Expressed Emotion (SAVEE) datasets respectively. For the combination of the two models, our proposed merging mechanism without re-training achieved an accuracy of close to 100% on both datasets. Finally, we demonstrated our system for a customer satisfaction use case in a real customer-to-salesperson interaction using audio and video models, achieving an average accuracy of 78%.

OtsikkoProceedings of 16th International Conference on Mobility, Sensing and Networking (MSN 2020)
ISBN (elektroninen)978-1-7281-9916-0
DOI - pysyväislinkit
TilaJulkaistu - huhtik. 2021
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaInternational Conference on Mobility, Sensing and Networking - Tokyo, Japani
Kesto: 17 jouluk. 202019 jouluk. 2020
Konferenssinumero: 16


ConferenceInternational Conference on Mobility, Sensing and Networking


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