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Wyszukujesz frazę "Igras-Cybulska, Magdalena" wg kryterium: Autor


Wyświetlanie 1-3 z 3
Tytuł:
Capturing emotions in voice: A comparative analysis of methodologies in psychology and digital signal processing
Autorzy:
Hekiert, Daniela
Igras-Cybulska, Magdalena
Powiązania:
https://bibliotekanauki.pl/articles/2125376.pdf
Data publikacji:
2019-11-19
Wydawca:
Katolicki Uniwersytet Lubelski Jana Pawła II. Towarzystwo Naukowe KUL
Tematy:
emotional vocalizations; emotional prosody; vocal bursts; process of encoding and decoding
emotional vocalizations
emotional prosody
vocal bursts
process of encoding and decoding
Opis:
People use their voices to communicate not only verbally but also emotionally. This article presents theories and methodologies that concern emotional vocalizations at the intersection of psychology and digital signal processing. Specifically, it demonstrates the encoding (production) and decoding (recognition) of emotional sounds, including the review and comparison of strategies in database design, parameterization, and classification. Whereas psychology predominantly focuses on the subjective recognition of emotional vocalizations, digital signal processing relies on automated and thus more objective vocal affect measures. The article aims to compare these two approaches and suggest methods of combining them to achieve a more complex insight into the vocal communication of emotions.
Źródło:
Roczniki Psychologiczne; 2019, 22, 1; 15-34
1507-7888
Pojawia się w:
Roczniki Psychologiczne
Dostawca treści:
Biblioteka Nauki
Artykuł
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
Artykuł
Tytuł:
Speech Analysis as a Tool for Detection and Monitoring of Medical Conditions : A review
Autorzy:
Igras-Cybulska, Magdalena
Hemmerling, Daria
Ziółko, Mariusz
Datka, Wojciech
Stogowska, Ewa
Kucharski, Michał
Rzepka, Rafał
Ziółko, Bartosz
Powiązania:
https://bibliotekanauki.pl/articles/31339837.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
speech analysis
speech features
acoustic parameters
linguistic analysis
voice biomarkers
screening test
Opis:
The goal of this article is to present and compare recent approaches which use speech and voice analysis as biomarkers for screening tests and monitoring of some diseases. The article takes into account metabolic, respiratory, cardiovascular, endocrine, and nervous system disorders. A selection of articles was performed to identify studies that assess voice features quantitatively in selected disorders by acoustic and linguistic voice analysis. Information was extracted from each paper in order to compare various aspects of datasets, speech parameters, methods of applied analysis and obtained results. 110 research papers were reviewed and 47 databases were summarized. Speech analysis is a promising method for early diagnosis of certain disorders. Advanced computer voice analysis with machine learning algorithms combined with the widespread availability of smartphones allows diagnostic analysis to be conducted during the patient’s visit to the doctor or at the patient’s home during a telephone conversation. Speech analysis is a simple, low-cost, non-invasive and easy-toprovide method of medical diagnosis. These are remarkable advantages, but there are also disadvantages. The effectiveness of disease diagnoses varies from 65% up to 99%. For that reason it should be treated as a medical screening test and should be an indication of the need for classic medical tests.
Źródło:
Archives of Acoustics; 2023, 48, 3; 289-315
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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