[HTML][HTML] Bio-acoustic features of depression: A review
SA Almaghrabi, SR Clark, M Baumert - Biomedical Signal Processing and …, 2023 - Elsevier
Speech carries essential information about the speaker's physiology and possible
pathophysiological conditions. Bio-acoustic voice qualities show promising value for …
pathophysiological conditions. Bio-acoustic voice qualities show promising value for …
Speech emotion recognition using convolution neural networks and multi-head convolutional transformer
Speech emotion recognition (SER) is a challenging task in human–computer interaction
(HCI) systems. One of the key challenges in speech emotion recognition is to extract the …
(HCI) systems. One of the key challenges in speech emotion recognition is to extract the …
Cross-corpus acoustic emotion recognition with multi-task learning: Seeking common ground while preserving differences
There is growing interest in emotion recognition due to its potential in many applications.
However, a pervasive challenge is the presence of data variability caused by factors such as …
However, a pervasive challenge is the presence of data variability caused by factors such as …
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 …
Multiscale amplitude feature and significance of enhanced vocal tract information for emotion classification
S Deb, S Dandapat - IEEE transactions on cybernetics, 2018 - ieeexplore.ieee.org
In this paper, a novel multiscale amplitude feature is proposed using multiresolution analysis
(MRA) and the significance of the vocal tract is investigated for emotion classification from …
(MRA) and the significance of the vocal tract is investigated for emotion classification from …
Compensating for speaker or lexical variabilities in speech for emotion recognition
S Mariooryad, C Busso - Speech Communication, 2014 - Elsevier
Affect recognition is a crucial requirement for future human machine interfaces to effectively
respond to nonverbal behaviors of the user. Speech emotion recognition systems analyze …
respond to nonverbal behaviors of the user. Speech emotion recognition systems analyze …
Comparing biosignal and acoustic feature representation for continuous emotion recognition
Automatic recognition of human emotion has a wide range of applications. Human emotions
can be identified across different modalities, such as biosignal, speech, text, and mimics …
can be identified across different modalities, such as biosignal, speech, text, and mimics …
Exploiting acoustic and lexical properties of phonemes to recognize valence from speech
Emotions modulate speech acoustics as well as language. The latter influences the
sequences of phonemes that are produced, which in turn further modulate the acoustics …
sequences of phonemes that are produced, which in turn further modulate the acoustics …
Continuous emotion recognition with phonetic syllables
As research on the extraction of acoustic properties of speech for emotion recognition
progresses, the need of investigating methods of feature extraction taking into account the …
progresses, the need of investigating methods of feature extraction taking into account the …
Combining relevance language modeling and clarity measure for extractive speech summarization
Extractive speech summarization, which purports to select an indicative set of sentences
from a spoken document so as to succinctly represent the most important aspects of the …
from a spoken document so as to succinctly represent the most important aspects of the …