19c96fd51791d8d23b94660 20211016060137133 beie:beie director@blueeyesintelligence.org WEB-FORM International Journal of Recent Technology and Engineering (IJRTE) IJRTE 22773878 10.35940/ijrte.2277-3878 https://www.ijrte.org/ 11 30 2021 10 4 10.35940/ijrte.10.4 https://www.ijrte.org/download/volume-10-issue-4/ School of Computer Science and Engineering, VIT Vellore, India. Aayush Gupta Anant Gandhi School of Computer Science and Engineering, VIT Vellore, India. Saarthak Agarwal School of Computer Science and Engineering, VIT Vellore, India, Shamin Chokshi School of Computer Science and Engineering, VIT Vellore, India Saravanakumar K School of Information Technology and Engineering, VIT Vellore, India The concept of Natural Language Processing that deals with problems of identifying the sentiment from the voice or text of a speaker or writer and then use that analysis further for making predictions, market survey, customer service, product satisfaction, precision targeting etc. is called Sentiment analysis. From one viewpoint, it is an abstract evaluation of something dependent on close to home observational experience. It Is mostly established in target realities and incompletely governed by feelings. Then again, a sentiment can be deciphered as a kind of measurement in the information in regards to a specific subject. It is a lot of markers that mix present a point of view, i.e., perspective for the specific issue. So as to enhance the accuracy of sentiment analysis/classification, it is imperative to appropriately recognize the semantic connections between the various words and phrases that are describing the subject or aspect. This can be done by applying semantic analysis with a syntactic parser and supposition vocabulary. This research will discuss different sets of approaches for application or domain specific problems and then compare them to obtain the best possible approaches to the problem of sentiment analysis. 11 30 2021 56 70 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.A1409.1110421 https://www.ijrte.org/wp-content/uploads/papers/v10i4/A1409059120.pdf School of Mechanical Engineering, Anhui University of Science and Technology, Huainan, China Mubashar Nawaz Xianhua Li School of Mechanical Engineering, Anhui University of Science and Technology, Huainan, China Sohaib Latif School of Mathematics and Big Data, Anhui University of Science and Technology, Huainan, China Sadaf Irshad School of Mathematics and Big Data, Anhui University of Science and Technology, Huainan, China Shabnam Sarwar School of Mathematics and Big Data, Anhui University of Science and Technology, Huainan, China More than 110 million people in this world are facing some kind of disability, for which they experience difficulty while eating food. Eating Assistive Robots could meet the needs of the elderly and people with upper limb disabilities or dysfunctions in gaining independence in eating. We are researching making a robot, which can assist the disabled in eating their meals. Our Eating Assistive Robot will detect the face of the disabled and process it for whether his/her mouth is opened or closed. Our robot will put a pre-prepared replaceable spoon of food in his/her mouth iteratively until the food lasts in the food container. The methodology we used for it i.e. firstly there is a live camera feed through which we are detecting human faces, after this, a library of Affectiva calculates how much mouth is open. We have set a certain threshold after which the program starts the stepper motor which brings the pre-filled spoon of food into the mouth of the disabled. 11 30 2021 71 77 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.D6543.1110421 https://www.ijrte.org/wp-content/uploads/papers/v10i4/D65431110421.pdf