Speech emotion recognition using support vector machine
M Jain, S Narayan, P Balaji, A Bhowmick… - arXiv preprint arXiv …, 2020 - arxiv.org
In this project, we aim to classify the speech taken as one of the four emotions namely,
sadness, anger, fear and happiness. The samples that have been taken to complete this …
sadness, anger, fear and happiness. The samples that have been taken to complete this …
Semantic segmentation of urban scenes by learning local class interactions
Traditionally, land-cover mapping from remote sensing images is performed by classifying
each atomic region in the image in isolation and by enforcing simple smoothing priors via …
each atomic region in the image in isolation and by enforcing simple smoothing priors via …
Class-level spectral features for emotion recognition
The most common approaches to automatic emotion recognition rely on utterance-level
prosodic features. Recent studies have shown that utterance-level statistics of segmental …
prosodic features. Recent studies have shown that utterance-level statistics of segmental …
Feature analysis and evaluation for automatic emotion identification in speech
The definition of parameters is a crucial step in the development of a system for identifying
emotions in speech. Although there is no agreement on which are the best features for this …
emotions in speech. Although there is no agreement on which are the best features for this …
[HTML][HTML] Enhancement of neurocognitive assessments using smartphone capabilities: Systematic review
JM Templeton, C Poellabauer… - JMIR mHealth and …, 2020 - mhealth.jmir.org
Background: Comprehensive exams such as the Dean-Woodcock Neuropsychological
Assessment System, the Global Deterioration Scale, and the Boston Diagnostic Aphasia …
Assessment System, the Global Deterioration Scale, and the Boston Diagnostic Aphasia …
Error weighted semi-coupled hidden Markov model for audio-visual emotion recognition
This paper presents an approach to the automatic recognition of human emotions from
audio-visual bimodal signals using an error weighted semi-coupled hidden Markov model …
audio-visual bimodal signals using an error weighted semi-coupled hidden Markov model …
Toward effective automatic recognition systems of emotion in speech
Humans are emotional beings, and emotions are one of the main drivers of human thoughts
and actions. Therefore, for all environments designed for humans, it is essential that emotion …
and actions. Therefore, for all environments designed for humans, it is essential that emotion …
Speech emotion recognition research: an analysis of research focus
This article analyses research in speech emotion recognition (“SER”) from 2006 to 2017 in
order to identify the current focus of research, and areas in which research is lacking. The …
order to identify the current focus of research, and areas in which research is lacking. The …
Comparison of different classifiers for emotion recognition
T Iliou, CN Anagnostopoulos - 2009 13th Panhellenic …, 2009 - ieeexplore.ieee.org
In the present paper a comparison of two classifiers for speech signal emotion recognition is
presented. Recognition was performed on emotional Berlin Database. Within this work we …
presented. Recognition was performed on emotional Berlin Database. Within this work we …
Affective communication through air jet stimulation: Evidence from event-related potentials
MY Tsalamlal, W Rizer, JC Martin… - International Journal of …, 2018 - Taylor & Francis
In this article, effectiveness of air jet stimulation in mediated emotional communication was
investigated by assessing cross-modal influences of visual emotional expressions on tactile …
investigated by assessing cross-modal influences of visual emotional expressions on tactile …