Emotion recognition and confidence ratings predicted by vocal stimulus type and acoustic parameters

2019 ◽  
Author(s):  
Adi Lausen ◽  
Kurt Hammerschmidt
Keyword(s):  
Emotion Recognition ◽  
Stimulus Type ◽  
Emotional Expressions ◽  
Acoustic Features ◽  
Acoustic Parameters ◽  
Performance Accuracy ◽  
The Impact ◽  
The Voice ◽  
Vocal Emotion

Human speech expresses emotional meaning not only through semantics, but also through certain attributes of the voice, such as pitch or loudness. In investigations of vocal emotion recognition, there is considerable variability in the types of stimuli and procedures used to examine their influence on emotion recognition. In addition, a person’s confidence in the assessments of another person’s emotional state has been argued to strongly influence performance accuracy in emotion recognition tasks. Nevertheless, such associations have rarely been studied previously. We addressed this gap by examining the impact of vocal stimulus type and prosodic speech attributes on emotion recognition and a person’s confidence in a given response. We analysed a total of 1038 emotional expressions according to a baseline set of 13 prosodic acoustic parameters. Results showed that these parameters provided sufficient discrimination between expressions of emotional categories to permit accurate statistical classification. Emotion recognition and confidence judgments were found to depend on stimulus material as they could be predicted by different constellations of acoustic features. Finally, results indicated that the correct classification of emotional expressions elicited increased confident judgments. Together, these findings show that vocal stimulus type and prosodic attributes of speech strongly influence emotion recognition and listeners’ confidence in these given responses.

Perception of Vowels and Dental Consonants in Bangla Speech Processing

2013 ◽  
pp. 246-272
Author(s):  
Syed Akhter Hossain ◽  
M. Lutfar Rahman ◽  
Faruk Ahmed ◽  
M. Abdus Sobhan
Keyword(s):  
Speech Enhancement ◽  
Automatic Speech Recognition ◽  
Speech Processing ◽  
Native Speakers ◽  
Problem Area ◽  
Acoustic Features ◽  
Acoustic Parameters ◽  
Independent Manner

The aim of this chapter is to clearly understand the salient features of Bangla vowels and the sources of acoustic variability in Bangla vowels, and to suggest classification of vowels based on normalized acoustic parameters. Possible applications in automatic speech recognition and speech enhancement have made the classification of vowels an important problem to study. However, Bangla vowels spoken by different native speakers show great variations in their respective formant values. This brings further complications in the acoustic comparison of vowels due to different dialect and language backgrounds of the speakers. This variation necessitates the use of normalization procedures to remove the effect of non-linguistic factors. Although several researchers found a number of acoustical and perceptual correlates of vowels, acoustic parameters that work well in a speaker-independent manner are yet to be found. Besides, study of acoustic features of Bangla dental consonants to identify the spectral differences between different consonants and to parameterize them for the synthesis of the segments is another problem area for study. The extracted features for both Bangla vowels and dental consonants are tested and found with good synthetic representations that demonstrate the quality of acoustic features.

scholarly journals Acoustic Identification of Sentence Accent in Speakers with Dysarthria: Cross-Population Validation and Severity Related Patterns

2021 ◽  
Vol 11 (10) ◽  
pp. 1344
Author(s):  
Viviana Mendoza Ramos ◽  
Anja Lowit ◽  
Leen Van den Steen ◽  
Hector Arturo Kairuz Hernandez-Diaz ◽  
Maria Esperanza Hernandez-Diaz Huici ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
English Speakers ◽  
Prosodic Features ◽  
Acoustic Features ◽  
Healthy Control ◽  
Severity Levels ◽  
Acoustic Identification ◽  
Automated Procedures ◽  
The Impact

Dysprosody is a hallmark of dysarthria, which can affect the intelligibility and naturalness of speech. This includes sentence accent, which helps to draw listeners’ attention to important information in the message. Although some studies have investigated this feature, we currently lack properly validated automated procedures that can distinguish between subtle performance differences observed across speakers with dysarthria. This study aims for cross-population validation of a set of acoustic features that have previously been shown to correlate with sentence accent. In addition, the impact of dysarthria severity levels on sentence accent production is investigated. Two groups of adults were analysed (Dutch and English speakers). Fifty-eight participants with dysarthria and 30 healthy control participants (HCP) produced sentences with varying accent positions. All speech samples were evaluated perceptually and analysed acoustically with an algorithm that extracts ten meaningful prosodic features and allows a classification between accented and unaccented syllables based on a linear combination of these parameters. The data were statistically analysed using discriminant analysis. Within the Dutch and English dysarthric population, the algorithm correctly identified 82.8 and 91.9% of the accented target syllables, respectively, indicating that the capacity to discriminate between accented and unaccented syllables in a sentence is consistent with perceptual impressions. Moreover, different strategies for accent production across dysarthria severity levels could be demonstrated, which is an important step toward a better understanding of the nature of the deficit and the automatic classification of dysarthria severity using prosodic features.

scholarly journals The impact of facemasks on emotion recognition, trust attribution and re-identification

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Marco Marini ◽  
Alessandro Ansani ◽  
Fabio Paglieri ◽  
Fausto Caruana ◽  
Marco Viola
Keyword(s):  
Emotion Recognition ◽  
Social Communication ◽  
Emotional Expressions ◽  
Mouth Region ◽  
Visual Access ◽  
The World ◽  
The Face ◽  
Face Reading ◽  
The Impact ◽  
Identity Processing

AbstractCovid-19 pandemics has fostered a pervasive use of facemasks all around the world. While they help in preventing infection, there are concerns related to the possible impact of facemasks on social communication. The present study investigates how emotion recognition, trust attribution and re-identification of faces differ when faces are seen without mask, with a standard medical facemask, and with a transparent facemask restoring visual access to the mouth region. Our results show that, in contrast to standard medical facemasks, transparent masks significantly spare the capability to recognize emotional expressions. Moreover, transparent masks spare the capability to infer trustworthiness from faces with respect to standard medical facemasks which, in turn, dampen the perceived untrustworthiness of faces. Remarkably, while transparent masks (unlike standard masks) do not impair emotion recognition and trust attribution, they seemingly do impair the subsequent re-identification of the same, unmasked, face (like standard masks). Taken together, this evidence supports a dissociation between mechanisms sustaining emotion and identity processing. This study represents a pivotal step in the much-needed analysis of face reading when the lower portion of the face is occluded by a facemask.

scholarly journals The Investigation the Effects of the Performance of an Independent Emotion Recognition of Model Used in the Dimensioning of Emotions

2016 ◽  
Vol 2 (3) ◽  
pp. 26
Author(s):  
Turgut Özseven ◽  
Muharrem Düğenci
Keyword(s):  
Emotion Recognition ◽  
Acoustic Analysis ◽  
Objective Evaluation ◽  
Dimensional Structure ◽  
Support Vector ◽  
Dimensional Model ◽  
Acoustic Parameters ◽  
Categorical Structure ◽  
Recognition Success ◽  
The Impact

Emotion recognition aims at determining the state of emotion which is included in the speech or mimics of a person. Emotion recognition from speech is an area related to signal processing and psychology. Acoustic parameters obtained from speech signals through acoustic analysis, which is one of objective evaluation methods, is intensively used in emotion recognition studies. In this paper success in emotion recognition is examined in categorical aspects and the impact of dimensional model on independent emotion recognition success is investigated. Acoustic parameters were subjected to classification with Support Vector Machine in order to determine emotion recognition success. According to the obtained findings, emotion recognition success in categorical structure, dimensional structure and categorical-dimensional structure were 69.5%, 73.3% and 87.1%, respectively. Even if dimensional structure is higher in arousal than in valence, when emotion recognition success is examined on each emotion dimension, valence provided higher success.

scholarly journals Facial Imitation Improves Emotion Recognition in Adults with Different Levels of Sub-Clinical Autistic Traits

2021 ◽  
Vol 9 (1) ◽  
pp. 4
Author(s):  
Andrea Kowallik ◽  
Maike Pohl ◽  
Stefan Schweinberger
Keyword(s):  
Emotion Recognition ◽  
Mirror Neuron System ◽  
Mirror Neuron ◽  
Recognition Task ◽  
Autistic Traits ◽  
Emotional Expressions ◽  
Neuron System ◽  
Computer Based ◽  
The Impact ◽  
Different Levels

We used computer-based automatic expression analysis to investigate the impact of imitation on facial emotion recognition with a baseline-intervention-retest design. The participants: 55 young adults with varying degrees of autistic traits, completed an emotion recognition task with images of faces displaying one of six basic emotional expressions. This task was then repeated with instructions to imitate the expressions. During the experiment, a camera captured the participants’ faces for an automatic evaluation of their imitation performance. The instruction to imitate enhanced imitation performance as well as emotion recognition. Of relevance, emotion recognition improvements in the imitation block were larger in people with higher levels of autistic traits, whereas imitation enhancements were independent of autistic traits. The finding that an imitation instruction improves emotion recognition, and that imitation is a positive within-participant predictor of recognition accuracy in the imitation block supports the idea of a link between motor expression and perception in the processing of emotions, which might be mediated by the mirror neuron system. However, because there was no evidence that people with higher autistic traits differ in their imitative behavior per se, their disproportional emotion recognition benefits could have arisen from indirect effects of imitation instructions

scholarly journals The Investigation the Effects of the Performance of an Independent Emotion Recognition of Model Used in the Dimensioning of Emotions

2016 ◽  
Vol 2 (3) ◽  
pp. 26
Author(s):  
Turgut Özseven ◽  
Muharrem Düğenci
Keyword(s):  
Emotion Recognition ◽  
Acoustic Analysis ◽  
Objective Evaluation ◽  
Dimensional Structure ◽  
Support Vector ◽  
Dimensional Model ◽  
Acoustic Parameters ◽  
Categorical Structure ◽  
Recognition Success ◽  
The Impact

Emotion recognition aims at determining the state of emotion which is included in the speech or mimics of a person. Emotion recognition from speech is an area related to signal processing and psychology. Acoustic parameters obtained from speech signals through acoustic analysis, which is one of objective evaluation methods, is intensively used in emotion recognition studies. In this paper success in emotion recognition is examined in categorical aspects and the impact of dimensional model on independent emotion recognition success is investigated. Acoustic parameters were subjected to classification with Support Vector Machine in order to determine emotion recognition success. According to the obtained findings, emotion recognition success in categorical structure, dimensional structure and categorical-dimensional structure were 69.5%, 73.3% and 87.1%, respectively. Even if dimensional structure is higher in arousal than in valence, when emotion recognition success is examined on each emotion dimension, valence provided higher success.

scholarly journals The Investigation the Effects of the Performance of an Independent Emotion Recognition of Model Used in the Dimensioning of Emotions

2016 ◽  
Vol 2 (3) ◽  
pp. 26
Author(s):  
Turgut Özseven ◽  
Muharrem Düğenci
Keyword(s):  
Emotion Recognition ◽  
Acoustic Analysis ◽  
Objective Evaluation ◽  
Dimensional Structure ◽  
Support Vector ◽  
Dimensional Model ◽  
Acoustic Parameters ◽  
Categorical Structure ◽  
Recognition Success ◽  
The Impact

Emotion recognition aims at determining the state of emotion which is included in the speech or mimics of a person. Emotion recognition from speech is an area related to signal processing and psychology. Acoustic parameters obtained from speech signals through acoustic analysis, which is one of objective evaluation methods, is intensively used in emotion recognition studies. In this paper success in emotion recognition is examined in categorical aspects and the impact of dimensional model on independent emotion recognition success is investigated. Acoustic parameters were subjected to classification with Support Vector Machine in order to determine emotion recognition success. According to the obtained findings, emotion recognition success in categorical structure, dimensional structure and categorical-dimensional structure were 69.5%, 73.3% and 87.1%, respectively. Even if dimensional structure is higher in arousal than in valence, when emotion recognition success is examined on each emotion dimension, valence provided higher success.

Face masks bolsters the characteristics from looking at a face even when facial expressions are impaired

2021 ◽  
Author(s):  
Wee Kiat Lau
Keyword(s):  
Social Interactions ◽  
Emotion Recognition ◽  
Facial Expressions ◽  
Online Survey ◽  
Emotional Expressions ◽  
Future Directions ◽  
The Face ◽  
Full Face ◽  
Post Hoc ◽  
The Impact

Face masks impact social interactions negatively because emotion recognition is difficult due to the occlusion by the masks. But is this enough to associate face masks to negative social interactions? We investigated the impact of face masks on invariant characteristics, trait-like characteristics, and emotional expressions for faces with and without face masks. Participants completed an online survey and rated masked and no-masked faces. Participants never saw the same face with and without masks. According to the results, when compared to no-masked faces, emotional expressions for masked faces were rated poorer. However, ratings for other characteristics were rated better for masked faces. This suggested that, while some aspects such as emotional expressions, were negatively impeded by face masks, other aspects were not affected the same way. Post-hoc modelling for trait-like characteristics also revealed that for some characteristics, the non-occluded region of the face helped us understand certain information about a person. Likewise, for other characteristics, the full face helped us gather certain information about the person. Collectively, the results, together with the literature, hinted at greater acceptance of face masks. There were better ratings for certain characteristics with face masks, despite worser ratings for emotion expressions. Therefore, face masks did not necessarily impact social interactions negatively. Future directions were proposed to expand the research.

scholarly journals The Investigation the Effects of the Performance of an Independent Emotion Recognition of Model Used in the Dimensioning of Emotions

2016 ◽  
Vol 5 (1) ◽  
pp. 26
Author(s):  
Turgut Özseven ◽  
Muharrem Düğenci
Keyword(s):  
Emotion Recognition ◽  
Acoustic Analysis ◽  
Objective Evaluation ◽  
Dimensional Structure ◽  
Support Vector ◽  
Dimensional Model ◽  
Acoustic Parameters ◽  
Categorical Structure ◽  
Recognition Success ◽  
The Impact

Emotion recognition aims at determining the state of emotion which is included in the speech or mimics of a person. Emotion recognition from speech is an area related to signal processing and psychology. Acoustic parameters obtained from speech signals through acoustic analysis, which is one of objective evaluation methods, is intensively used in emotion recognition studies. In this paper success in emotion recognition is examined in categorical aspects and the impact of dimensional model on independent emotion recognition success is investigated. Acoustic parameters were subjected to classification with Support Vector Machine in order to determine emotion recognition success. According to the obtained findings, emotion recognition success in categorical structure, dimensional structure and categorical-dimensional structure were 69.5%, 73.3% and 87.1%, respectively. Even if dimensional structure is higher in arousal than in valence, when emotion recognition success is examined on each emotion dimension, valence provided higher success.

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