Mobile application based speech and voice analysis for COVID-19 detection using computational audit techniques

Udhaya Sankar S.M., Ganesan R., Jeevaa Katiravan, R. M, Ruhin Kouser R.
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引用次数: 19

Abstract

PurposeIt has been six months from the time the first case was registered, and nations are still working on counter steering regulations. The proposed model in the paper encompasses a novel methodology to equip systems with artificial intelligence and computational audition techniques over voice recognition for detecting the symptoms. Regular and irregular speech/voice patterns are recognized using in-built tools and devices on a hand-held device. Phenomenal patterns can be contextually varied among normal and presence of asymptotic symptoms.Design/methodology/approachThe lives of patients and healthy beings are seriously affected with various precautionary measures and social distancing. The spread of virus infection is mitigated with necessary actions by governments and nations. Resulting in increased death ratio, the novel coronavirus is certainly a serious pandemic which spreads with unhygienic practices and contact with air-borne droplets of infected patients. With minimal measures to detect the symptoms from the early onset and the rise of asymptotic outcomes, coronavirus becomes even difficult for detection and diagnosis.FindingsA number of significant parameters are considered for the analysis, and they are dry cough, wet cough, sneezing, speech under a blocked nose or cold, sleeplessness, pain in chests, eating behaviours and other potential cases of the disease. Risk- and symptom-based measurements are imposed to deliver a symptom subsiding diagnosis plan. Monitoring and tracking down the symptoms inflicted areas, social distancing and its outcomes, treatments, planning and delivery of healthy food intake, immunity improvement measures are other areas of potential guidelines to mitigate the disease.Originality/valueThis paper also lists the challenges in actual scenarios for a solution to work satisfactorily. Emphasizing on the early detection of symptoms, this work highlights the importance of such a mechanism in the absence of medication or vaccine and demand for large-scale screening. A mobile and ubiquitous application is definitely a useful measure of alerting the officials to take necessary actions by eliminating the expensive modes of tests and medical investigations.
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基于移动应用程序的语音和语音分析,使用计算审计技术进行COVID-19检测
从第一例案例登记到现在已经过去了6个月,各国仍在制定反驾驶法规。本文提出的模型包括一种新的方法,使系统具备人工智能和计算试听技术,而不是语音识别,以检测症状。使用手持设备上的内置工具和设备识别规则和不规则的语音/语音模式。现象模式可以在正常和无症状的情况下有所不同。设计/方法/方法各种预防措施和保持社会距离严重影响病人和健康人的生命。政府和国家采取必要行动,减轻病毒感染的传播。新型冠状病毒是一种严重的大流行,它通过不卫生的做法和接触感染者的空气飞沫传播,导致死亡率上升。由于从早期发病开始检测症状的措施很少,而且无症状结果的增加,冠状病毒的检测和诊断变得更加困难。在分析中考虑了一些重要的参数,它们是干咳、湿咳、打喷嚏、鼻塞或感冒、失眠、胸痛、饮食行为和其他潜在的疾病病例。采用基于风险和症状的测量来提供症状消退诊断计划。监测和追踪造成症状的地区、保持社交距离及其结果、治疗、规划和提供健康食物摄入、提高免疫力措施是减轻疾病的潜在指导方针的其他领域。原创性/价值本文还列出了解决方案在实际场景中令人满意地工作的挑战。这项工作强调早期发现症状,强调了这种机制在缺乏药物或疫苗和大规模筛查需求的情况下的重要性。移动和无处不在的应用程序绝对是一个有用的措施,提醒官员采取必要的行动,消除昂贵的测试和医疗调查模式。
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