V. Ryali, Sristi Kumari, SyedMuhammad Anwar, Dr. Sheela S V
{"title":"Empathetic Robot for the Elderly using Machine Learning","authors":"V. Ryali, Sristi Kumari, SyedMuhammad Anwar, Dr. Sheela S V","doi":"10.35940/ijsce.c3578.0712322","DOIUrl":null,"url":null,"abstract":"According to WHO estimates, there is a growing population of over 1 billion people aged above 60 years of age. There has been an increasing shortage of caregivers for the aging populations. This has opened a market of USD 7 billion dollars in senior care alone. In a struggle to care for our elderly and capitalize from this industry in efficiency, this paper presents an empathetic robot that can make day-to-day activities hassle free. It is a voice assistant that can detect the emotion of the speaker and reply with contextual awareness to bridge the superstitious gap between the elderly and technology. It achieves this with multi-modal classification of emotion using audio and text. i) Machine learning model using Librosa to engineer features and Support vector classifier (SVC) , ii) BERT based model using transfer learning to categorize text. The robot can also set reminders for appointments and medicine intake to help with forgetfulness. The robot is customizable by a caregiver or loved one through the web application where details of any messages, reminders, descriptions of prescriptions could be entered. The robot comes with a pill dispenser that can rotate and dispense pills at the correct time and also notify the senior through the speaker. A raspberry pi is used to convert the speech to text and vice versa. The design of this robot paves the path to providing a realistic, care-giving experience to the elderly.","PeriodicalId":173799,"journal":{"name":"International Journal of Soft Computing and Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Soft Computing and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.35940/ijsce.c3578.0712322","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
According to WHO estimates, there is a growing population of over 1 billion people aged above 60 years of age. There has been an increasing shortage of caregivers for the aging populations. This has opened a market of USD 7 billion dollars in senior care alone. In a struggle to care for our elderly and capitalize from this industry in efficiency, this paper presents an empathetic robot that can make day-to-day activities hassle free. It is a voice assistant that can detect the emotion of the speaker and reply with contextual awareness to bridge the superstitious gap between the elderly and technology. It achieves this with multi-modal classification of emotion using audio and text. i) Machine learning model using Librosa to engineer features and Support vector classifier (SVC) , ii) BERT based model using transfer learning to categorize text. The robot can also set reminders for appointments and medicine intake to help with forgetfulness. The robot is customizable by a caregiver or loved one through the web application where details of any messages, reminders, descriptions of prescriptions could be entered. The robot comes with a pill dispenser that can rotate and dispense pills at the correct time and also notify the senior through the speaker. A raspberry pi is used to convert the speech to text and vice versa. The design of this robot paves the path to providing a realistic, care-giving experience to the elderly.