Speech emotion recognition

By Björn Schuller. Communications of the ACM, 2018

531 citations recorded by the source corpus.

How researchers see this paper

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Engaged to a Robot? The Role of AI in Service (2020, background): “The latter high-touch service promises to benefit from feeling AI by analyzing, recognizing, and understanding customer emotions (Schuller 2018), and responding and serving them in an emotionally appropriate manner on an individual customer basis.”
Emotional Voice Conversion: Theory, Databases and ESD (2021, background): “However, it has not adequately equipped with human-like emotions (Schuller and Schuller, 2018).”
Speech Emotion Recognition Using Deep Learning Techniques: A Review (2019, background): “there are many problems in HCI systems that still need to be properly addressed, particularly as these systems move from lab testing to real-world application [8]–[10].”
A Systematic Review on Affective Computing: Emotion Models, Databases, and Recent Advances (2022, background): “In the combination of CNNs and RNNs, ConvNet-RNN networks with the cascaded fusion [230,283] or the ensemble strategy [215] have been proposed for FER, by simultaneously capturing textural and temporal information.”