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pro vyhledávání: '"Devillers, Laurence"'
Speech emotion recognition (SER) has received a great deal of attention in recent years in the context of spontaneous conversations. While there have been notable results on datasets like the well known corpus of naturalistic dyadic conversations, IE
Externí odkaz:
http://arxiv.org/abs/2401.00536
Autor:
Feng, Yajing, Devillers, Laurence
Publikováno v:
2023 11th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW), Sep 2023, Boston (MA), United States
Speech Emotion recognition (SER) in call center conversations has emerged as a valuable tool for assessing the quality of interactions between clients and agents. In contrast to controlled laboratory environments, real-life conversations take place u
Externí odkaz:
http://arxiv.org/abs/2310.02281
Multiscale Contextual Learning for Speech Emotion Recognition in Emergency Call Center Conversations
Emotion recognition in conversations is essential for ensuring advanced human-machine interactions. However, creating robust and accurate emotion recognition systems in real life is challenging, mainly due to the scarcity of emotion datasets collecte
Externí odkaz:
http://arxiv.org/abs/2308.14894
Exploring Attention Mechanisms for Multimodal Emotion Recognition in an Emergency Call Center Corpus
Publikováno v:
Published in ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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 small. The experiments conducted in this paper use the CEMO, which wa
Externí odkaz:
http://arxiv.org/abs/2306.07115
Publikováno v:
2021 9th International Conference on Affective Computing and Intelligent Interaction (ACII), Sep 2021, Nara, Japan
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 equivalent or even better results than conventional machine learning approac
Externí odkaz:
http://arxiv.org/abs/2110.14957
Akademický článek
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Autor:
Etienne, Caroline, Fidanza, Guillaume, Petrovskii, Andrei, Devillers, Laurence, Schmauch, Benoit
Publikováno v:
Workshop on Speech, Music and Mind 2018
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 involving both convolutional layers, for extracting high-level features fro
Externí odkaz:
http://arxiv.org/abs/1802.05630
Publikováno v:
Langages; jun2024, Issue 234, p117-134, 18p
Akademický článek
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Autor:
Grinbaum, Alexei, Chatila, Raja, Devillers, Laurence, Martin, Caroline, Kirchner, Claude, Perrin, Jérôme, Tessier, Catherine
Publikováno v:
Comité national pilote d'éthique du numérique. 2023, pp.Avis 7 du CNPEN
Cet avis du Comité national pilote d’éthique du numérique (CNPEN) répond à la saisine du ministre délégué chargé de la Transition numérique et des Télécommunications, en date du 20 février 2023. Il est consacré à l’examen des quest
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::6e951d5430ed4e2c286fbc4b162ba462
https://cea.hal.science/cea-04153216
https://cea.hal.science/cea-04153216