DE eng

Search in the Catalogues and Directories

Page: 1 2 3 4 5...72
Hits 1 – 20 of 1.424

1
Emotional Speech Recognition Using Deep Neural Networks
In: ISSN: 1424-8220 ; Sensors ; https://hal.archives-ouvertes.fr/hal-03632853 ; Sensors, MDPI, 2022, 22 (4), pp.1414. ⟨10.3390/s22041414⟩ (2022)
BASE
Show details
2
Emotion on a textual level: the structuring function of emotions observed from annotations ; L'émotion à un niveau textuel : la fonction structurante des émotions observée à partir d'annotations
In: ISSN: 1963-1723 ; Discours - Revue de linguistique, psycholinguistique et informatique ; https://hal.archives-ouvertes.fr/hal-03607564 ; Discours - Revue de linguistique, psycholinguistique et informatique, Laboratoire LATTICE, A paraître (2022)
BASE
Show details
3
ELAL: An Emotion Lexicon for the Analysis of Alsatian Theatre Plays
In: Language Resources and Evaluation Conference ; https://hal.archives-ouvertes.fr/hal-03655148 ; Language Resources and Evaluation Conference, Jun 2022, Marseille, France ; https://lrec2022.lrec-conf.org/ (2022)
BASE
Show details
4
The role of actors, targets, and witnesses: Examining gratitude exchanges in a social context
In: JOURNAL OF POSITIVE PSYCHOLOGY, vol 17, iss 2 (2022)
BASE
Show details
5
Evaluation of Speaker Anonymization on Emotional Speech ; Analyse de l'anonymisation du locuteur sur de la parole émotionnelle
In: JEP2022 - Journées d'Études sur la Parole ; https://hal.archives-ouvertes.fr/hal-03636737 ; JEP2022 - Journées d'Études sur la Parole, Jun 2022, Île de Noirmoutier, France (2022)
BASE
Show details
6
Contextual time-continuous emotion recognition based on multimodal data ...
Fedotov, Dmitrii. - : Universität Ulm, 2022
BASE
Show details
7
The Effect of Self-Distancing on Emotion Regulation and Autobiographical Remembering ...
Dilek, Senanur. - : Open Science Framework, 2022
BASE
Show details
8
К ВОПРОСУ ИЗУЧЕНИЯ МИМИКИ В ЛИНГВИСТИКЕ ...
Моҳинурхон Ахрорхон Қизи Иброҳимова. - : Academic research in educational sciences, 2022
BASE
Show details
9
Psychic Life-Biological Molecule Bidirectional Relationship: Pathways, Mechanisms, and Consequences for Medical and Psychological Sciences—A Narrative Review
In: International Journal of Molecular Sciences; Volume 23; Issue 7; Pages: 3932 (2022)
BASE
Show details
10
Data for: Prosodic alignment toward emotionally expressive speech: Comparing human and Alexa model talkers ...
Cohn, Michelle. - : Mendeley, 2022
BASE
Show details
11
Linking Categorical and Dimensional Approaches to Assess Food-Related Emotions
In: Foods; Volume 11; Issue 7; Pages: 972 (2022)
BASE
Show details
12
Perceived Anger in Clear and Conversational Speech: Contributions of Age and Hearing Loss
In: Brain Sciences; Volume 12; Issue 2; Pages: 210 (2022)
BASE
Show details
13
In a Bilingual Mood: Mood Affects Lexico-Semantic Processing Differently in Native and Non-Native Languages
In: Brain Sciences; Volume 12; Issue 3; Pages: 316 (2022)
BASE
Show details
14
Emotion Understanding in Bilingual Preschoolers
In: Behavioral Sciences; Volume 12; Issue 4; Pages: 115 (2022)
BASE
Show details
15
Emotional Speech Recognition Method Based on Word Transcription
In: Sensors; Volume 22; Issue 5; Pages: 1937 (2022)
BASE
Show details
16
Affective State Recognition in Livestock—Artificial Intelligence Approaches
In: Animals; Volume 12; Issue 6; Pages: 759 (2022)
Abstract: Farm animals, numbering over 70 billion worldwide, are increasingly managed in large-scale, intensive farms. With both public awareness and scientific evidence growing that farm animals experience suffering, as well as affective states such as fear, frustration and distress, there is an urgent need to develop efficient and accurate methods for monitoring their welfare. At present, there are not scientifically validated ‘benchmarks’ for quantifying transient emotional (affective) states in farm animals, and no established measures of good welfare, only indicators of poor welfare, such as injury, pain and fear. Conventional approaches to monitoring livestock welfare are time-consuming, interrupt farming processes and involve subjective judgments. Biometric sensor data enabled by artificial intelligence is an emerging smart solution to unobtrusively monitoring livestock, but its potential for quantifying affective states and ground-breaking solutions in their application are yet to be realized. This review provides innovative methods for collecting big data on farm animal emotions, which can be used to train artificial intelligence models to classify, quantify and predict affective states in individual pigs and cows. Extending this to the group level, social network analysis can be applied to model emotional dynamics and contagion among animals. Finally, ‘digital twins’ of animals capable of simulating and predicting their affective states and behaviour in real time are a near-term possibility.
Keyword: affective states; animal emotions; animal welfare; animal-based measures; emotion modelling; sensors
URL: https://doi.org/10.3390/ani12060759
BASE
Hide details
17
Estimating the Emotional Information in Japanese Songs Using Search Engines
In: Sensors; Volume 22; Issue 5; Pages: 1800 (2022)
BASE
Show details
18
Emotional Speech Recognition Using Deep Neural Networks
In: Sensors; Volume 22; Issue 4; Pages: 1414 (2022)
BASE
Show details
19
A Multitask Learning Framework for Abuse Detection and Emotion Classification
In: Algorithms; Volume 15; Issue 4; Pages: 116 (2022)
BASE
Show details
20
Advanced Fusion-Based Speech Emotion Recognition System Using a Dual-Attention Mechanism with Conv-Caps and Bi-GRU Features
In: Electronics; Volume 11; Issue 9; Pages: 1328 (2022)
BASE
Show details

Page: 1 2 3 4 5...72

Catalogues
1
0
4
0
0
0
11
Bibliographies
5
0
0
0
0
0
0
0
0
Linked Open Data catalogues
0
Online resources
21
3
1
0
Open access documents
1.385
2
0
0
0
© 2013 - 2024 Lin|gu|is|tik | Imprint | Privacy Policy | Datenschutzeinstellungen ändern