Results 211 to 220 of about 71,334 (264)

Sex-dependent cortico-amygdala circuits controlling emotion recognition

González-Parra JA, Ayuso-Jimeno IP, Chang X, Somoza-Cotillas P, Acciai V, Canela-Grimau M, Vidal-Palencia L, Tan L, Deng B, Papaleo F, Schumann G, Busquets-Garcia A.   +11 more
europepmc   +1 more source

The Recognition of Emotion [PDF]

, 2000
To detect emotional user behavior, particularly anger, can be very useful for successful automatic dialog processing. We present databases and prosodic classifiers implemented for the recognition of emotion in Verbmobil. Using a prosodic feature vector alone is, however, not sufficient for the modelling of emotional user behavior.
Batliner, Anton, Huber, Richard, Niemann, Heinrich, Nöth, Elmar, Spilker, Jörg, Fischer, Kerstin   +5 more
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Bimodal emotion recognition

Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580), 2002
This paper describes the use of statistical techniques and hidden Markov models (HMM) in the recognition of emotions. The method aims to classify 6 basic emotions (anger, dislike, fear, happiness, sadness and surprise) from both facial expressions (video) and emotional speech (audio). The emotions of 2 human subjects were recorded and analyzed.
Liyanage C. De Silva, Pei Chi Ng
openaire   +1 more source

Cerebellum and Emotion Recognition

2022
In this chapter, after having clarified which definition of emotion we followed, starting from Darwin and evolutionary psychology, we tried to examine the main mechanisms of emotional recognition from a behavioral and cerebral point of view: emotional contagion and cognitive empathy. The link between these skills and social cognition has been discussed.
D'Agata, Federico, Orsi, Laura
openaire   +2 more sources

Distant Emotion Recognition

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2017
Distant emotion recognition (DER) extends the application of speech emotion recognition to the very challenging situation that is determined by variable speaker to microphone distances. The performance of conventional emotion recognition systems degrades dramatically as soon as the microphone is moved away from the mouth of the speaker.
Asif Salekin, Zeya Chen, Mohsin Y. Ahmed, John C. Lach, Donna Spruijt-Metz, Kayla de la Haye, Brooke Bell, John A. Stankovic   +7 more
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Emotion Recognition in Context

2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
Understanding what a person is experiencing from her frame of reference is essential in our everyday life. For this reason, one can think that machines with this type of ability would interact better with people. However, there are no current systems capable of understanding in detail peoples emotional states.
Ronak Kosti, José M. Álvarez 0004, Adrià Recasens, Àgata Lapedriza   +3 more
openaire   +2 more sources

Incremental emotion recognition

Interspeech 2013, 2013
Most emotion recognition systems do not perform real-time emotion recognition due to latencies caused by phrase segmentation and resource-intensive feature acquisition, etc. To address this issue, we present an emotion recognition approach that can estimate speaker emotions with much lower latency.
Taniya Mishra, Dimitrios Dimitriadis
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Bimodal Emotion Recognition

2010
When interacting with robots we show a plethora of affective reactions typical of natural communications. Indeed, emotions are embedded on our communications and represent a predominant communication channel to convey relevant, high impact, information.
Marco Paleari, Ryad Chellali, Benoit Huet   +2 more
openaire   +1 more source