【採択】学部3年生 泉川君の研究が国際会議ACM HotMobile 2023 poster sessionにacceptされました – ‘ Audio-based Eating Stage Recognition through CNN Model Trained on ASMR Eating Sounds’

Abstract:

A balanced diet and an appropriate calorie intake are the keys to both preventing and treating type II diabetes. Meanwhile, widespread techniques such as manual food logs and food image captures have been posing burdens on those with diabetes and have made diet monitoring difficult to become part of one’s routine. To develop an earable device that monitors a volume of food intake automatically, an-audio based detection of eating instances is necessary. The present research therefore attempted to classify an eating sound, collected from YouTube eating ASMR, into one of the following labels: chew, swallow, or non-eating A CNN machine learning model using sound features as input achieved an accuracy of 81%.