153 citations · 166 across the 4 of their papers we have counts for
4 papers
Multiscale Contextual Learning for Speech Emotion Recognition in Emergency Call Center Conversations
Théo Deschamps-Berger, Lori Lamel, Laurence Devillers
Emotion recognition in conversations is essential for ensuring advanced human-machine interactions. However, creating robust and accurate emotion recognition systems in real life i…
Exploring Attention Mechanisms for Multimodal Emotion Recognition in an Emergency Call Center Corpus
Théo Deschamps-Berger, Lori Lamel, Laurence Devillers
The emotion detection technology to enhance human decision-making is an important research issue for real-world applications, but real-life emotion datasets are relatively rare and…
End-to-End Speech Emotion Recognition: Challenges of Real-Life Emergency Call Centers Data Recordings
Théo Deschamps-Berger, Lori Lamel, Laurence Devillers
Recognizing a speaker's emotion from their speech can be a key element in emergency call centers. End-to-end deep learning systems for speech emotion recognition now achieve equiva…
CNN+LSTM Architecture for Speech Emotion Recognition with Data Augmentation
Caroline Etienne, Guillaume Fidanza, Andrei Petrovskii +2
In this work we design a neural network for recognizing emotions in speech, using the IEMOCAP dataset. Following the latest advances in audio analysis, we use an architecture invol…