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Mental status assessment of disaster relief personnel by vocal affect display based on voice emotion recognition

机译:基于语音情感识别的语音情感展示对救灾人员心理状态的评估

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BackgroundDisaster relief personnel tend to be exposed to excessive stress, which can be a cause of mental disorders. To prevent from mental disorders, frequent assessment of mental status is important. This pilot study aimed to examine feasibility of stress assessment using vocal affect display (VAD) indices as calculated by our proposed algorithms in a situation of comparison between different durations of stay in stricken area as disaster relief operation, which is an environment highly likely to induce stress. MethodsWe used Sensibility Technology (ST) software to analyze VAD from voices of participants exposed to extreme stress for either long or short durations, and we proposed algorithms for indices of low VAD (VAD-L), high VAD (VAD-H), and VAD ratio (VAD-R), calculated from the intensity of emotions as measured by voice emotion analysis. As a preliminary validation, 12 members of Japan Self-Defense Forces dispatched overseas for long (3?months or more) or short (about a week) durations were asked to record their voices saying 11 phrases repeatedly across 6?days during their dispatch. ResultsIn the validation, the two groups showed an inverse relationship in VAD-L and VAD-H, in that long durations in disaster zones resulted in higher values of both VAD-L and VAD-R, and lower values of VAD-H, compared with short durations. Interestingly, phrases produced varied results in terms of group differences and VAD indices, demonstrating the sensitivity of the ST. ConclusionsA comparison of the values obtained for the different groups of subjects clarified that there were tendencies of the VAD-L, VAD-H, and VAD-R indices observed for each group of participants. The results suggest the possibility of using ST software in the measurement of affective aspects related to mental health from vocal behavior.
机译:背景技术救灾人员往往会承受过度的压力,这可能是精神障碍的原因。为了预防精神障碍,经常评估精神状态很重要。这项前瞻性研究旨在检验在受灾地区不同停留时间(如救灾行动)之间进行比较的情况下,使用我们提出的算法计算出的使用声音影响显示(VAD)指数进行压力评估的可行性。强调。方法我们使用敏感性技术(ST)软件从长时间或短期内承受极端压力的参与者的声音中分析VAD,并提出了针对低VAD(VAD-L),高VAD(VAD-H)和VAD比(VAD-R),根据语音情感分析所测量的情感强度来计算。作为初步验证,日本自卫队的12名成员在海外派遣了很长(3个月或更长时间)或短暂(大约一周)的时间,被要求录制声音,在派遣期间的6天内重复说11个短语。结果在验证中,两组的VAD-L和VAD-H呈反比关系,因为在灾区中持续时间较长,导致VAD-L和VAD-R的值均较高,而VAD-H的值较低持续时间短。有趣的是,短语在组差异和VAD指数方面产生了不同的结果,表明了ST的敏感性。结论对不同组受试者获得的值进行的比较表明,每组参与者均存在VAD-L,VAD-H和VAD-R指数的趋势。结果表明,可以使用ST软件测量与声音行为有关的心理健康相关的情感方面。

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