Browsing by Author "Noroozi, Fatemeh"
Now showing items 1-5 of 5
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Audio-Visual Emotion Recognition in Video Clips
Anbarjafari, Gholamreza; Noroozi, Fatemeh; Marjanovic, Marina; Njegus, Angelina; Escalera, Sergio (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2019-01)This paper presents a multimodal emotion recognition system, which is based on the analysis of audio and visual cues. From the audio channel, Mel-Frequency Cepstral Coefficients, Filter Bank Energies and prosodic features ... -
Automatic speech based emotion recognition using paralinguistics features
Hook, Jarnes; Noroozi, Fatemeh; Toygar, Onsen; Anbarjafari, Gholamreza (POLSKA AKAD NAUK, 2019)Affective computing studies and develops systems capable of detecting humans affects. The search for universal well-performing features for speech-based emotion recognition is ongoing. In this paper, a small set of features ... -
Supervised Vocal-Based Emotion Recognition Using Multiclass Support Vector Machine, Random Forests, and Adaboost
Anbarjafari, Gholamreza; Noroozi, Fatemeh; Kaminska, Dorota; Sapinski, Tomasz (AUDIO ENGINEERING SOC, 2017-07)This paper investigates and compares three different classifiers-multi-class Support Vector Machine, Adaboost, and random forests-for the purpose of vocal emotion recognition. Additionally, the decisions of all classifiers ... -
Survey on Emotional Body Gesture Recognition
Noroozi, Fatemeh; Corneanu, Ciprian Adrian; Kaminska, Dorota; Sapinski, Tomasz; Escalera, Sergio; Anbarjafari, Gholamreza (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, APR-JUN 20)Automatic emotion recognition has become a trending research topic in the past decade. While works based on facial expressions or speech abound, recognizing affect from body gestures remains a less explored topic. We present ... -
Vocal-based emotion recognition using random forests and decision tree
Anbarjafari, Gholamreza; Noroozi, Fatemeh; Sapinski, Tomasz; Kaminska, Dorota (SPRINGER, 2017-06)This paper proposes a new vocal-based emotion recognition method using random forests, where pairs of the features on the whole speech signal, namely, pitch, intensity, the first four formants, the first four formants ...
