Automatic children’s personality assessment from emotional speech

Pérez-Espinosa, Humberto; Gutiérrez-Serafín, Benjamín; Martı́nez-Miranda, Juan; Espinosa-Curiel, Ismael Edrein

doi:10.1016/j.eswa.2021.115885

Cited by 10 publications

(7 citation statements)

References 32 publications

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“…In 2015, Yegnanarayana and Gangashetty added echo features to recognize the differences in the LP residual energy in speech emotion and found that echo features were conducive to the characterization of emotion in segmented speech and were beneficial to improve the recognition rate [5]. In 2017, Gangamohan et al achieved identification rates of 76 and 69% on the IITH-H and EMO-DB databases, respectively, by calculating the Kullback-Leibler (KL) distance of the excitation source signals [6]. In 2019, Pravena and Govind determined the intensity of the excitation source and the base frequency of the speech signal and calculated its statistical properties using the Gaussian Mixture Model (GMM), which further improved the efficiency of the identification of these excitation source features [7].…”

Section: Excitation Source Featuresmentioning

confidence: 99%

Design of the Speech Emotion Recognition Model

Luo

Shi

2023

Ieee Iceib 2023

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Section: Excitation Source Featuresmentioning

confidence: 99%

Design of the Speech Emotion Recognition Model

Luo

Shi

2023

Ieee Iceib 2023

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“…Talent acquisition and talent management consider psychometric profiling an important step as many business leaders have admitted that mindset is more important than skill-set in a dependable candidate. 2 The most recent domains that researchers have started looking into to understand the personality of person are facial cues, 3,4 speech, 5 handwriting 6 and oddball questions. 7 Some new fields where the use of personality profiling is proposed is cyber threat intelligence, where Reference 8 found out that the personality of each hacker is correlated with the pattern of their hacking and their expertise level.…”

Section: Introductionmentioning

confidence: 99%

“…The most recent domains that researchers have started looking into to understand the personality of person are facial cues, 3,4 speech, 5 handwriting 6 and oddball questions 7 . Some new fields where the use of personality profiling is proposed is cyber threat intelligence, where Reference 8 found out that the personality of each hacker is correlated with the pattern of their hacking and their expertise level.…”

Section: Introductionmentioning

confidence: 99%

Psychometric profiling of individuals using Twitter profiles: A psychological Natural Language Processing based approach

Rathi

Verma

Jain³

et al. 2022

Concurrency and Computation

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The recent pandemic saw the operations of many businesses shifting to virtual mode. Tasks like psychometric analysis of individuals, for various applications, are conducted online. In this article, we introduce a novel system to analyze the semantics of an individual's tweets from their Twitter profile using LIWC and SALLEE scores. These scores can be used to evaluate less fortunate, thin‐filed candidates using their Twitter profiles. With increased access to phones and the internet, many organizations are focusing on making credit systems available to the masses by introducing psychometric analysis. This article proposes a dynamic model for evaluating the personality of a Twitter user using the textual content shared on their page. The model will allow stakeholders to ascertain the personality of user according to any personality model. To analyze if this is viable and flexible approach to model any kind of personality model, we take MBTI personality dataset and train classifier to predict personality types. Then these results are correlated with a linguistic score to find correlation between the two. We found that proposed approach, outperformed the other relevant works also some aspects of these linguistic scores show a heavy correlation with certain personality types.

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“…The emotion recognition system is also valuable for interactive educational systems, which can be able to truthfully identify a child’s emotions that helps for positive evaluations [ 3 ]. Moreover, it is used to automatically classify the children’s personalities through their speech when they are interacting with computers [ 4 ]. However, detecting emotions from speech is a big challenging task in the field of artificial intelligence and human-machine interface application [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

Bidirectional parallel echo state network for speech emotion recognition

Ibrahim

Loo

Alnajjar

2022

Neural Comput & Applic

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Speech is an effective way for communicating and exchanging complex information between humans. Speech signal has involved a great attention in human-computer interaction. Therefore, emotion recognition from speech has become a hot research topic in the field of interacting machines with humans. In this paper, we proposed a novel speech emotion recognition system by adopting multivariate time series handcrafted feature representation from speech signals. Bidirectional echo state network with two parallel reservoir layers has been applied to capture additional independent information. The parallel reservoirs produce multiple representations for each direction from the bidirectional data with two stages of concatenation. The sparse random projection approach has been adopted to reduce the high-dimensional sparse output for each direction separately from both reservoirs. Random over-sampling and random under-sampling methods are used to overcome the imbalanced nature of the used speech emotion datasets. The performance of the proposed parallel ESN model is evaluated from the speaker-independent experiments on EMO-DB, SAVEE, RAVDESS, and FAU Aibo datasets. The results show that the proposed SER model is superior to the single reservoir and the state-of-the-art studies.

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Automatic children’s personality assessment from emotional speech

Cited by 10 publications

References 32 publications

Design of the Speech Emotion Recognition Model

Design of the Speech Emotion Recognition Model

Psychometric profiling of individuals using Twitter profiles: A psychological Natural Language Processing based approach

Bidirectional parallel echo state network for speech emotion recognition

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