• Science of Emotion and Sensibility
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• v.24 no.1
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• pp.91-104
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• 2021

This study explored users' emotional states identified from the wake-up words -"Hi, KIA!"- using a machine learning algorithm considering the user interface of passenger cars' voice. We targeted four emotional states, namely, excited, angry, desperate, and neutral, and created a total of 12 emotional scenarios in the context of car driving. Nine college students participated and recorded sentences as guided in the visualized scenario. The wake-up words were extracted from whole sentences, resulting in two data sets. We used the soundgen package and svmRadial method of caret package in open source-based R code to collect acoustic features of the recorded voices and performed machine learning-based analysis to determine the predictability of the modeled algorithm. We compared the accuracy of wake-up words (60.19%: 22%~81%) with that of whole sentences (41.51%) for all nine participants in relation to the four emotional categories. Accuracy and sensitivity performance of individual differences were noticeable, while the selected features were relatively constant. This study provides empirical evidence regarding the potential application of the wake-up words in the practice of emotion-driven user experience in communication between users and the artificial intelligence system.

• Phonetics and Speech Sciences
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• v.15 no.4
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• pp.45-51
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• 2023

Voice issues such as voice weakness that arise with age can have social and emotional impacts, potentially leading to feelings of isolation and depression. This study aimed to investigate the changes in acoustic characteristics resulting from aging, focusing on voice quality and spoken fluency. To this end, tasks involving sustained vowel phonation and paragraph reading were recorded for 20 elderly and 20 young participants. Voice-quality-related variables, including F0, jitter, shimmer, and Cepstral Peak Prominence (CPP) values, were analyzed along with speech-fluency-related variables, such as average syllable duration (ASD), articulation rate (AR), and speech rate (SR). The results showed that in voice quality-related measurements, F0 was higher for the elderly and voice quality was diminished, as indicated by increased jitter, shimmer, and lower CPP levels. Speech fluency analysis also demonstrated that the elderly spoke more slowly, as indicated by all ASD, AR, and SR measurements. Correlation analysis between voice quality and speech fluency showed a significant relationship between shimmer and CPP values and between ASD and SR values. This suggests that changes in spoken fluency can be identified early by measuring the variations in voice quality. This study further highlights the reciprocal relationship between voice quality and spoken fluency, emphasizing that deterioration in one can affect the other.

• Journal of Oral Medicine and Pain
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• v.30 no.4
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• pp.427-432
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• 2005

This study have been compared and analyzed voice parameter under the condition of normal voice and auditory condition(noise and music) for 29 patients of orofacial pain and 31 normal people to investigate voice feature and vocal variation for auditory condition of orofacial pain patient. 1. Compared to normal voice, orofacial pain patient showed lower and unstable voice feature which has low F0 rate and high jitter and shimmer rate. 2. Voice of orofacial pain patient showed more relaxed and stable voice feature with low F0 and shimmer rate in the music condition than noise condition. 3. Normal people's voice has no significant difference between music and noise condition even though it has high F0 rate under the noise condition. As a result, orofacial pain patient showed difference of feature and different response for external auditory condition compared to normal voice. Providing of positive emotional environment such as music could be considered for better outcome of oral facial pain patient's functional disability.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.16 no.1
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• pp.23-27
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• 2005

Background and Objectives : Voice disorders can cause problems in patients with benign vocal cord lesions emotionally, physically, economically and functionally. Neither subjective nor objective voice examinations can evaluate such factors adequately. The Voice Handicap Index (VHI) subjectively evaluates voice disorders in terms of physical, functional, emotional factors and measures the patient's perception of the impact of voice disorder. The purpose of this study is to evaluate the usefulness of VHI in the patients with benign vocal cord lesions. Materials and Method : The authors evaluated 37 patients who experienced laryngeal microsurgery for benign vocal cord lesions from september 2003 to August 2004. The VHI was used to measure the postoperative changes of the patient's perception and acoustic analysis and aerodynamic tests were also done. Statistical analysis was done using paired t-test and Pearson's correlation. Results : The VHI scores showed statistically significant reductions postoperatively. In acoustic analysis, jitter and shimmer had statistically significant reductions after surgery but noise-to-harmonics ratio did not. A statistically significant change in the average MFR and MPT perioperatively was found. The relationship between VHI and acoustic, aerodynamic analysis attained statistical significance. Conclusion : The VHI is a useful assessment tool to monitor the patient's self-perception of voice change after the surgery of benign vocal cord lesions. The VHI measurement, when combined with acoustic and aerodynamic analyses, will be helpful in comparing functional outcomes after voice surgery.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.63-72
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• 2018

The human voice is one of the easiest methods for the information transmission between human beings. The characteristics of voice can vary from person to person and include the speed of speech, the form and function of the vocal organ, the pitch tone, speech habits, and gender. The human voice is a key element of human communication. In the days of the Fourth Industrial Revolution, voices are also a major means of communication between humans and humans, between humans and machines, machines and machines. And for that reason, people are trying to communicate their intentions to others clearly. And in the process, it contains various additional information along with the linguistic information. The Information such as emotional status, health status, part of trust, presence of a lie, change due to drinking, etc. These linguistic and non-linguistic information can be used as a device for evaluating the individual's credit worthiness by appearing in various parameters through voice analysis. Especially, it can be obtained by analyzing the relationship between the characteristics of the fundamental frequency(basic tonality) of the vocal cords, and the characteristics of the resonance frequency of the vocal track.In the previous research, the necessity of various methods of credit evaluation and the characteristic change of the voice according to the change of credit status were studied. In this study, we propose a personal credit discriminator by machine learning through parameters extracted through voice.

• Journal of English Language & Literature
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• v.55 no.6
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• pp.993-1011
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• 2009

Generally, the parts narrated by Esther in Bleak House has been considered less convincing and reliable than those by the anonymous narrator for some problematic qualities in her character and narration. However, Esther's narrative shows Dickens' masterly depiction of emotional deprivation, the psychic consequences of the Victorian sexual repression on its victim. Therefore, to restore the reliability of Esther's narrative is the prerequisite for claiming its value as an appropriate locus of the meanings of the text. On the other hand, the anonymous narrator is not so omniscient as he has been regarded. As the chapters proceed, his omniscient power and authority is conspicuously weakened, and even transferred to other characters such as Esther and Mr. Bucket. This shows that the identity of the omniscient voice is unstable and that Dickens does not intend his voice to be the sole center of meanings of the text. In short, these two narratives are the necessary partners in imagining and understanding the society in its wholeness. Alternating and sometimes intersecting each other throughout the novel, these opposing viewpoints make us see the contradictory multi-leveledness of the Victorian society. The equality of them implies Dickens' notion that more than single unified voice is needed to portray ideological conflicts of his age.

• Korean Journal of Bronchoesophagology
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• v.9 no.1
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• pp.83-86
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• 2003

Background and Objectives : Paradoxical vocal cord movement is a series of paroxysmal adduction of the anterior two-thirds of the vocal cords during respiration or during phonation. The choking, stridor, and wheezing in this condition occur primarily on inhalation, rather than on exhalation. The two pathognomonic diagnostic criterias that need to be assessed during an acute presentation are laryngoscopy with direct visualization of paradoxical adduction of the vocal cords and pulmonary function testing. Materials and Methods : A retrospective review of 3 patients who were referred to otolaryngologist from pulmonology department, and were confirmed by typical laryngoscopic findings with paradoxical adduction of the vocal cords was conducted. Results The patients were misdiagnosed as exercised-induced asthma, and unresponsive to corticosteroid and bronchodilators. Improvement was achieved only by diagnosis with paradoxial vocal cord movement. Biofeed back therapy, voice therapy, treatment for reflux laryngitis improved symptoms. Conclusion The etiology of paradoxical vocal cord movement is unknown. It may be functional or emotional. The functional factors that were proposed are neurologic deficit and gastroesophageal reflux. Management methods of this condition consist of psychological counselling, voice therapy, and antireflux medication.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.391-393
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• 2019

본 논문은 일상적인 대화로부터 감성을 추출하고 분석함으로써 상황에 맞는 대화의 내용과 분위기를 이미지의 색상으로 표현할 수 있는 이미지 색상 변환 프레임워크를 소개한다. 본 연구는 라즈베리 파이와 마이크 센서를 기반으로 사용자로부터 목소리를 입력받을 수 있는 모듈을 제작하고, 그 목소리로부터 감성을 분석한다. 분석된 감성을 이용하여 이미지의 색상을 자동으로 변환하는 기술과 통합함으로써 청각장애인 및 미취학 아동들이 화자의 대화를 이미지를 통해 쉽게 인지하여 의사소통 및 감성 전달 환경을 개선하고자 한다.

• Journal of the Ergonomics Society of Korea
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• v.31 no.2
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• pp.271-279
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• 2012

Objective: This study classified three different emotional states(boredom, pain, and surprise) using physiological signals. Background: Emotion recognition studies have tried to recognize human emotion by using physiological signals. It is important for emotion recognition to apply on human-computer interaction system for emotion detection. Method: 122 college students participated in this experiment. Three different emotional stimuli were presented to participants and physiological signals, i.e., EDA(Electrodermal Activity), SKT(Skin Temperature), PPG(Photoplethysmogram), and ECG (Electrocardiogram) were measured for 1 minute as baseline and for 1~1.5 minutes during emotional state. The obtained signals were analyzed for 30 seconds from the baseline and the emotional state and 27 features were extracted from these signals. Statistical analysis for emotion classification were done by DFA(discriminant function analysis) (SPSS 15.0) by using the difference values subtracting baseline values from the emotional state. Results: The result showed that physiological responses during emotional states were significantly differed as compared to during baseline. Also, an accuracy rate of emotion classification was 84.7%. Conclusion: Our study have identified that emotions were classified by various physiological signals. However, future study is needed to obtain additional signals from other modalities such as facial expression, face temperature, or voice to improve classification rate and to examine the stability and reliability of this result compare with accuracy of emotion classification using other algorithms. Application: This could help emotion recognition studies lead to better chance to recognize various human emotions by using physiological signals as well as is able to be applied on human-computer interaction system for emotion recognition. Also, it can be useful in developing an emotion theory, or profiling emotion-specific physiological responses as well as establishing the basis for emotion recognition system in human-computer interaction.

• Journal of the Korean Society of Fashion and Beauty
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• v.6 no.1
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• pp.1-15
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• 2008

Beauty Art typically has been viewed as the best way to represent women's beauty. Specifically, nail art is a mean for the new generation to unveil their individuality. Nail-shop customers usually feel refreshed, and that emotional change gives them aesthetic and emotional satisfaction. The popularization of nail art and the growth of nail-art market arises the people's concern to the necessity of marketing strategy as part of the beauty industry, as well as the importance of service quality and customer satisfaction. The purpose of this study is to examine women's changing view of nail care and relevant consumption behavior. Also to analyze the voice of customers about the quality of services provided by nail shops, and to have the right understanding of the industry and as well as to determine some of the right directions for marketing.