Temat: emotion recognition - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: The relationship between Trait Emotional Intelligence and emotion recognition in the context of COVID-19 pandemic
Autorzy:: Cannavò, Marco
Barberis, Nadia
Larcan, Rosalba
Cuzzocrea, Francesca
Powiązania:: https://bibliotekanauki.pl/articles/2121465.pdf
Data publikacji:: 2022
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: COVID-19
Trait EI
emotion recognition
Opis:: Covid-19 pandemic is severely impacting worldwide. A line of research warned that facial occlusion may impair facial emotion recognition, whilst prior research highlighted the role of Trait Emotional Intelligence in the recognition of non-verbal social stimuli. The sample consisted of 102 emerging adults, aged 18-24 (M = 20.76; SD = 2.10; 84% females, 16% males) and were asked to recognize four different emotions (happiness, fear, anger, and sadness) in fully visible faces and in faces wearing a mask and to complete a questionnaire assessing Trait Emotional Intelligence. Results highlighted that individuals displayed lower accuracy in detecting happiness and fear in covered faces, while also being more inaccurate in reporting correct answers. The results show that subjects provide more correct answers when the photos show people without a mask than when they are wearing it. In addition, participants give more wrong answers when there are subjects wearing masks in the photos than when they are not wearing it. In addition, participants provide more correct answers regarding happiness and sadness when in the photos the subjects are not wearing the mask, compared to when they are wearing it. Implications are discussed.
Źródło:: Polish Psychological Bulletin; 2022, 53, 1; 15-22
0079-2993
Pojawia się w:: Polish Psychological Bulletin
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Analysis of Features and Classifiers in Emotion Recognition Systems : Case Study of Slavic Languages
Autorzy:: Nedeljković, Željko
Milošević, Milana
Ðurović, Željko
Powiązania:: https://bibliotekanauki.pl/articles/176678.pdf
Data publikacji:: 2020
Wydawca:: Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:: emotion recognition
speech processing
classification algorithms
Opis:: Today’s human-computer interaction systems have a broad variety of applications in which automatic human emotion recognition is of great interest. Literature contains many different, more or less successful forms of these systems. This work emerged as an attempt to clarify which speech features are the most informative, which classification structure is the most convenient for this type of tasks, and the degree to which the results are influenced by database size, quality and cultural characteristic of a language. The research is presented as the case study on Slavic languages.
Źródło:: Archives of Acoustics; 2020, 45, 1; 129-140
0137-5075
Pojawia się w:: Archives of Acoustics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: The Acoustic Cues of Fear : Investigation of Acoustic Parameters of Speech Containing Fear
Autorzy:: Özseven, T.
Powiązania:: https://bibliotekanauki.pl/articles/178133.pdf
Data publikacji:: 2018
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: emotion recognition
acoustic analysis
fear
speech processing
Opis:: Speech emotion recognition is an important part of human-machine interaction studies. The acoustic analysis method is used for emotion recognition through speech. An emotion does not cause changes on all acoustic parameters. Rather, the acoustic parameters affected by emotion vary depending on the emotion type. In this context, the emotion-based variability of acoustic parameters is still a current field of study. The purpose of this study is to investigate the acoustic parameters that fear affects and the extent of their influence. For this purpose, various acoustic parameters were obtained from speech records containing fear and neutral emotions. The change according to the emotional states of these parameters was analyzed using statistical methods, and the parameters and the degree of influence that the fear emotion affected were determined. According to the results obtained, the majority of acoustic parameters that fear affects vary according to the used data. However, it has been demonstrated that formant frequencies, mel-frequency cepstral coefficients, and jitter parameters can define the fear emotion independent of the data used.
Źródło:: Archives of Acoustics; 2018, 43, 2; 245-251
0137-5075
Pojawia się w:: Archives of Acoustics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Speech emotion recognition under white noise
Autorzy:: Huang, C.
Chen, G.
Yu, H.
Bao, Y.
Zhao, L.
Powiązania:: https://bibliotekanauki.pl/articles/177301.pdf
Data publikacji:: 2013
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: speech emotion recognition
speech enhancement
emotion model
Gaussian mixture model
Opis:: Speaker‘s emotional states are recognized from speech signal with Additive white Gaussian noise (AWGN). The influence of white noise on a typical emotion recogniztion system is studied. The emotion classifier is implemented with Gaussian mixture model (GMM). A Chinese speech emotion database is used for training and testing, which includes nine emotion classes (e.g. happiness, sadness, anger, surprise, fear, anxiety, hesitation, confidence and neutral state). Two speech enhancement algorithms are introduced for improved emotion classification. In the experiments, the Gaussian mixture model is trained on the clean speech data, while tested under AWGN with various signal to noise ratios (SNRs). The emotion class model and the dimension space model are both adopted for the evaluation of the emotion recognition system. Regarding the emotion class model, the nine emotion classes are classified. Considering the dimension space model, the arousal dimension and the valence dimension are classified into positive regions or negative regions. The experimental results show that the speech enhancement algorithms constantly improve the performance of our emotion recognition system under various SNRs, and the positive emotions are more likely to be miss-classified as negative emotions under white noise environment.
Źródło:: Archives of Acoustics; 2013, 38, 4; 457-463
0137-5075
Pojawia się w:: Archives of Acoustics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: Communication atmosphere in humans and robots interaction based on the concept of fuzzy atmosfield generated by emotional states of humans and robots
Autorzy:: Liu, Z. T.
Chen, L. F.
Dong, F. Y.
Hirota, K.
Min, W.
Li, D. Y.
Yamazaki, Y.
Powiązania:: https://bibliotekanauki.pl/articles/384920.pdf
Data publikacji:: 2013
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: human-robot interaction
communication atmosphere
fuzzy logic
emotion recognition
Opis:: Communication atmosphere based on emotional states of humans and robots is modeled by using Fuzzy Atmosfield (FA), where the human emotion is estimated from bimodal communication cues (i.e., speech and gesture) using weighted fusion and fuzzy logic, and the robot emotion is generated by emotional expression synthesis. It makes possible to quantitatively express overall affective expression of individuals, and helps to facilitate smooth communication in humans-robots interaction. Experiments in a household environment are performed by four humans and five eye robots, where emotion recognition of humans based on bimodal cues achieves 84% accuracy in average, improved by about 10% compared to that using only speech. Experimental results from the model of communication atmosphere based on the FA are evaluated by comparing with questionnaire surveys, from which the maximum error of 0.25 and the minimum correlation coefficient of 0.72 for three axes in the FA confirm the validity of the proposal. In ongoing work, an atmosphere representation system is being planned for casual communication between humans and robots, taking into account multiple emotional modalities such as speech, gesture, and music.
Źródło:: Journal of Automation Mobile Robotics and Intelligent Systems; 2013, 7, 2; 52-63
1897-8649
2080-2145
Pojawia się w:: Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 6.

Tytuł:: Multi-objective heuristic feature selection for speech-based multilingual emotion recognition
Autorzy:: Brester, C.
Semenkin, E.
Sidorov, M.
Powiązania:: https://bibliotekanauki.pl/articles/91588.pdf
Data publikacji:: 2016
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: multi-objective optimization
feature selection
speech-based emotion recognition
Opis:: If conventional feature selection methods do not show sufficient effectiveness, alternative algorithmic schemes might be used. In this paper we propose an evolutionary feature selection technique based on the two-criterion optimization model. To diminish the drawbacks of genetic algorithms, which are applied as optimizers, we design a parallel multicriteria heuristic procedure based on an island model. The performance of the proposed approach was investigated on the Speech-based Emotion Recognition Problem, which reflects one of the most essential points in the sphere of human-machine communications. A number of multilingual corpora (German, English and Japanese) were involved in the experiments. According to the results obtained, a high level of emotion recognition was achieved (up to a 12.97% relative improvement compared with the best F-score value on the full set of attributes).
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2016, 6, 4; 243-253
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 7.

Tytuł:: Emotion monitoring – verification of physiological characteristics measurement procedures
Autorzy:: Landowska, A.
Powiązania:: https://bibliotekanauki.pl/articles/220577.pdf
Data publikacji:: 2014
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: affective computing
emotion recognition
physiology
motion artifacts
sensor location
Opis:: This paper concerns measurement procedures on an emotion monitoring stand designed for tracking human emotions in the Human-Computer Interaction with physiological characteristics. The paper addresses the key problem of physiological measurements being disturbed by a motion typical for human-computer interaction such as keyboard typing or mouse movements. An original experiment is described, that aimed at practical evaluation of measurement procedures performed at the emotion monitoring stand constructed at GUT. Different locations of sensors were considered and evaluated for suitability and measurement precision in the Human- Computer Interaction monitoring. Alternative locations (ear lobes and forearms) for skin conductance, blood volume pulse and temperature sensors were proposed and verified. Alternative locations proved correlation with traditional locations as well as lower sensitiveness to movements like typing or mouse moving, therefore they can make a better solution for monitoring the Human-Computer Interaction.
Źródło:: Metrology and Measurement Systems; 2014, 21, 4; 719-732
0860-8229
Pojawia się w:: Metrology and Measurement Systems
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 8.

Tytuł:: Acoustic Methods in Identifying Symptoms of Emotional States
Autorzy:: Piątek, Zuzanna
Kłaczyński, Maciej
Powiązania:: https://bibliotekanauki.pl/articles/1953482.pdf
Data publikacji:: 2021
Wydawca:: Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:: emotion recognition
speech signal processing
clustering analysis
Sammon mapping
Opis:: The study investigates the use of speech signal to recognise speakers’ emotional states. The introduction includes the definition and categorization of emotions, including facial expressions, speech and physiological signals. For the purpose of this work, a proprietary resource of emotionally-marked speech recordings was created. The collected recordings come from the media, including live journalistic broadcasts, which show spontaneous emotional reactions to real-time stimuli. For the purpose of signal speech analysis, a specific script was written in Python. Its algorithm includes the parameterization of speech recordings and determination of features correlated with emotional content in speech. After the parametrization process, data clustering was performed to allows for the grouping of feature vectors for speakers into greater collections which imitate specific emotional states. Using the t-Student test for dependent samples, some descriptors were distinguished, which identified significant differences in the values of features between emotional states. Some potential applications for this research were proposed, as well as other development directions for future studies of the topic.
Źródło:: Archives of Acoustics; 2021, 46, 2; 259-269
0137-5075
Pojawia się w:: Archives of Acoustics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 9.

Tytuł:: Speech emotion recognition system for social robots
Autorzy:: Juszkiewicz, Ł.
Powiązania:: https://bibliotekanauki.pl/articles/384511.pdf
Data publikacji:: 2013
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: speech emotion recognition
prosody
machine learning
Emo-DB
intonation
social robot
Opis:: The paper presents a speech emotion recognition system for social robots. Emotions are recognised using global acoustic features of the speech. The system implements the speech parameters calculation, features extraction, features selection and classification. All these phases are described. The system was verified using the two emotional speech databases: Polish and German. Perspectives for using such system in the social robots are presented.
Źródło:: Journal of Automation Mobile Robotics and Intelligent Systems; 2013, 7, 4; 59-65
1897-8649
2080-2145
Pojawia się w:: Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 10.

Tytuł:: Speech Emotion Recognition Based on Voice Fundamental Frequency
Autorzy:: Dimitrova-Grekow, Teodora
Klis, Aneta
Igras-Cybulska, Magdalena
Powiązania:: https://bibliotekanauki.pl/articles/177227.pdf
Data publikacji:: 2019
Wydawca:: Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:: emotion recognition
speech signal analysis
voice analysis
fundamental frequency
speech corpora
Opis:: The human voice is one of the basic means of communication, thanks to which one also can easily convey the emotional state. This paper presents experiments on emotion recognition in human speech based on the fundamental frequency. AGH Emotional Speech Corpus was used. This database consists of audio samples of seven emotions acted by 12 different speakers (6 female and 6 male). We explored phrases of all the emotions – all together and in various combinations. Fast Fourier Transformation and magnitude spectrum analysis were applied to extract the fundamental tone out of the speech audio samples. After extraction of several statistical features of the fundamental frequency, we studied if they carry information on the emotional state of the speaker applying different AI methods. Analysis of the outcome data was conducted with classifiers: K-Nearest Neighbours with local induction, Random Forest, Bagging, JRip, and Random Subspace Method from algorithms collection for data mining WEKA. The results prove that the fundamental frequency is a prospective choice for further experiments.
Źródło:: Archives of Acoustics; 2019, 44, 2; 277-286
0137-5075
Pojawia się w:: Archives of Acoustics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 11.

Tytuł:: Facial emotion recognition using average face ratios and fuzzy hamming distance
Autorzy:: Ounachad, Khalid
Oualla, Mohamed
Sadiq, Abdelalim
Souhar, Abdelghani
Powiązania:: https://bibliotekanauki.pl/articles/2141894.pdf
Data publikacji:: 2020
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: average face ratios
facial emotion recognition
fuzzy hamming distance
perfect face ratios
Opis:: Facial emotion recognition (FER) is an important topic in the fields of computer vision and artificial intelligence owing to its significant academic and commercial potential. Nowadays, emotional factors are important as classic functional aspects of customer purchasing behavior. Purchasing choices and decisions making are the result of a careful analysis of the product advantages and disadvantages and of affective and emotional aspects. This paper presents a novel method for human emotion classification and recognition. We generate seven referential faces suitable for each kind of facial emotion based on perfect face ratios and some classical averages. The basic idea is to extract perfect face ratios for emotional face and for each referential face as features and calculate the distance between them by using fuzzy hamming distance. To extract perfect face ratios, we use the point landmarks in the face then sixteen features will be extract. An experimental evaluation demonstrates the satisfactory performance of our approach on WSEFEP dataset. It can be applied with any existing facial emotion dataset. The proposed algorithm will be a competitor of the other proposed relative approaches. The recognition rate reaches more than 90%.
Źródło:: Journal of Automation Mobile Robotics and Intelligent Systems; 2020, 14, 4; 37-44
1897-8649
2080-2145
Pojawia się w:: Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 12.

Tytuł:: Zastosowanie multimodalnej klasyfikacji w rozpoznawaniu stanów emocjonalnych na podstawie mowy spontanicznej
Spontaneus emotion redognition from speech signal using multimodal classification
Autorzy:: Kamińska, D.
Pelikant, A.
Powiązania:: https://bibliotekanauki.pl/articles/408014.pdf
Data publikacji:: 2012
Wydawca:: Politechnika Lubelska. Wydawnictwo Politechniki Lubelskiej
Tematy:: rozpoznawanie emocji
sygnał mowy
algorytm kNN
emotion recognition
speech signal
k-NN algorithm
Opis:: Artykuł prezentuje zagadnienie związane z rozpoznawaniem stanów emocjonalnych na podstawie analizy sygnału mowy. Na potrzeby badań stworzona została polska baza mowy spontanicznej, zawierająca wypowiedzi kilkudziesięciu osób, w różnym wieku i różnej płci. Na podstawie analizy sygnału mowy stworzono przestrzeń cech. Klasyfikację stanowi multimodalny mechanizm rozpoznawania, oparty na algorytmie kNN. Średnia poprawność: rozpoznawania wynosi 83%.
The article presents the issue of emotion recognition from a speech signal. For this study, a Polish spontaneous database, containing speech from people of different age and gender, was created. Features were determined from the speech signal. The process of recognition was based on multimodal classification, related to kNN algorithm. The average of accuracy performance was up to 83%.
Źródło:: Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska; 2012, 3; 36-39
2083-0157
2391-6761
Pojawia się w:: Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 13.

Tytuł:: Pomiary parametrów akustycznych mowy emocjonalnej - krok ku modelowaniu wokalnej ekspresji emocji
Measurements of emotional speech acoustic parameters - a step towards vocal emotion expression modelling
Autorzy:: Igras, M.
Wszołek, W.
Powiązania:: https://bibliotekanauki.pl/articles/154905.pdf
Data publikacji:: 2012
Wydawca:: Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:: rozpoznawanie emocji
wokalne korelaty emocji
przetwarzanie sygnału mowy
emotion recognition
vocal correlates of emotions
Opis:: Niniejsza praca podejmuje próbę pomiaru cech sygnału mowy skorelownych z jego zawartością emocjonalną (na przykładzie emocji podstawowych). Zaprezentowano korpus mowy zaprojektowany tak, by umożliwić różnicową analizę niezależną od mówcy i treści oraz przeprowadzono testy mające na celu ocenę jego przydatności do automatyzacji wykrywania emocji w mowie. Zaproponowano robocze profile wokalne emocji. Artykuł prezentuje również propozycje aplikacji medycznych opartych na pomiarach emocji w głosie.
The paper presents an approach to creating new measures of emotional content of speech signals. The results of this project constitute the basis or further research in this field. For analysis of differences of the basic emotional states independently of a speaker and semantic content, a corpus of acted emotional speech was designed and recorded. The alternative methods for emotional speech signal acquisition are presented and discussed (Section 2). Preliminary tests were performed to evaluate the corpus applicability to automatic emotion recognition. On the stage of recording labeling, human perceptual tests were applied (using recordings with and without semantic content). The results are presented in the form of the confusion table (Tabs. 1 and 2). The further signal processing: parametrisation and feature extraction techniques (Section 3) allowed extracting a set of features characteristic for each emotion, and led to developing preliminary vocal emotion profiles (sets of acoustic features characteristic for each of basic emotions) - an example is presented in Tab. 3. Using selected feature vectors, the methods for automatic classification (k nearest neighbours and self organizing neural network) were tested. Section 4 contains the conclusions: analysis of variables associated with vocal expression of emotions and challenges in further development. The paper also discusses use of the results of this kind of research for medical applications (Section 5).
Źródło:: Pomiary Automatyka Kontrola; 2012, R. 58, nr 4, 4; 335-338
0032-4140
Pojawia się w:: Pomiary Automatyka Kontrola
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 14.

Tytuł:: Speech emotion recognition based on sparse representation
Autorzy:: Yan, J.
Wang, X.
Gu, W.
Ma, L.
Powiązania:: https://bibliotekanauki.pl/articles/177778.pdf
Data publikacji:: 2013
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: speech emotion recognition
sparse partial least squares regression SPLSR
SPLSR
feature selection and dimensionality reduction
Opis:: Speech emotion recognition is deemed to be a meaningful and intractable issue among a number of do- mains comprising sentiment analysis, computer science, pedagogy, and so on. In this study, we investigate speech emotion recognition based on sparse partial least squares regression (SPLSR) approach in depth. We make use of the sparse partial least squares regression method to implement the feature selection and dimensionality reduction on the whole acquired speech emotion features. By the means of exploiting the SPLSR method, the component parts of those redundant and meaningless speech emotion features are lessened to zero while those serviceable and informative speech emotion features are maintained and selected to the following classification step. A number of tests on Berlin database reveal that the recogni- tion rate of the SPLSR method can reach up to 79.23% and is superior to other compared dimensionality reduction methods.
Źródło:: Archives of Acoustics; 2013, 38, 4; 465-470
0137-5075
Pojawia się w:: Archives of Acoustics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 15.

Tytuł:: Rozumienie mowy jako moderator związku rozpoznawania emocji z nasileniem symptomów zaburzeń ze spektrum autyzmu (ASD)
Autorzy:: Krzysztofik, Karolina
Powiązania:: https://bibliotekanauki.pl/articles/2054372.pdf
Data publikacji:: 2021
Wydawca:: Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej
Tematy:: autism spectrum disorder
ASD
emotion recognition
speech comprehension
zaburzenia ze spektrum autyzmu
rozpoznawanie emocji
rozumienie mowy
Opis:: Współcześni badacze podkreślają konsekwencje trudności osób z zaburzeniami ze spektrum autyzmu (Autism Spectrum Disorder, ASD) w rozpoznawaniu emocji dla nasilenia symptomów tego zaburzenia. Jednocześnie wiele z osób z ASD potrafi rozpoznawać emocje innych osób dzięki strategiom kompensacyjnym opartym na relatywnie dobrze rozwiniętych kompetencjach poznawczych i językowych. Wydaje się zatem, że umiejętności językowe osób z ASD mogą moderować związek rozpoznawania emocji z nasileniem symptomów ASD. Celem prezentowanych badań było ustalenie, czy poziom rozumienia mowy osób z ASD moderuje związek rozpoznawania emocji z nasileniem symptomów ASD. Przebadano grupę 63 dzieci z ASD w wieku od 3 lat i 7 miesięcy do 9 lat i 3 miesiący, wykorzystując następujące narzędzia: Skalę Nasilenia Symptomów ASD, podskalę Rozpoznawanie Emocji ze Skali Mechanizmu Teorii Umysłu oraz podskalę Rozumienie Mowy ze skali Iloraz Inteligencji i Rozwoju dla Dzieci w Wieku Przedszkolnym (IDS-P). Uzyskane wyniki wskazują, że poziom rozumienia mowy moderuje związek poziomu rozwoju rozpoznawania emocji z nasileniem symptomów ASD w zakresie deficytów w komunikowaniu i interakcjach. Wyniki te znajdują swoje implikacje dla włączenia terapii rozumienia mowy w proces rehabilitacji osób z ASD, a także dla teoretycznej refleksji nad uwarunkowaniami nasilenia symptomów ASD.
Contemporary researchers underline consequences of difficulties in emotion recognition experienced by persons with autism spectrum disorder (ASD) for severity of symptoms of this disorder. Individuals with ASD, when trying to recognize the emotional states of others, often use compensatory strategies based on relatively well-developed cognitive and linguistic competences. Thus, the relationship between the recognition of emotions and the severity of ASD symptoms may be moderated by linguistic competencies. Own research was aimed at determining if the level of speech comprehension moderates the relationship between emotion recognition and ASD symptom severity. Participants were 63 children with ASD aged from 3 years and 7 months to 9 years and 3 months. The following tools were used: ASD Symptom Severity Scale, the Emotion Recognition subscale of the Theory of Mind Scale and the Speech Comprehension subscale from the Intelligence and Development Scales – Preschool (IDS-P). The results indicate that the level of speech comprehension moderates the relationship between the level of emotion recognition and ASD symptom severity in the range of deficits in communication and interaction. These results have implications for integrating speech comprehension therapy into the process of the rehabilitation of individuals with ASD, as well as for theoretical reflection concerning the determinants of ASD symptom severity.
Źródło:: Annales Universitatis Mariae Curie-Skłodowska, sectio J – Paedagogia-Psychologia; 2021, 34, 3; 199-219
0867-2040
Pojawia się w:: Annales Universitatis Mariae Curie-Skłodowska, sectio J – Paedagogia-Psychologia
Dostawca treści:: Biblioteka Nauki

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