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Voice controlled mobile app helps you lose weight
A mobile application developed by US scientists lets you log calorie counts at every meal by verbally describing the contents of a meal, thus making it easier for people struggling with obesity to track their nutrition intake. Researchers at the Massachusets Institute of Technology (MIT) developed the app to make meal logging easier for people who don\'t have the time to find and record all the inf
New York: A mobile application developed by US scientists lets you log calorie counts at every meal by verbally describing the contents of a meal, thus making it easier for people struggling with obesity to track their nutrition intake. Researchers at the Massachusets Institute of Technology (MIT) developed the app to make meal logging easier for people who don't have the time to find and record all the information they need.
A web-based prototype of the speech-controlled nutrition-logging system was presented recently by the researchers at the International Conference on Acoustics, Speech, and Signal Processing in Shanghai. The app allows the user to verbally describe the contents of a meal, and the system parses the description and automatically retrieves the pertinent nutritional data from an online database maintained by the US Department of Agriculture.
The data is displayed together with images of the corresponding foods and pull-down menus that allow the user to refine their descriptions -- selecting, for instance, precise quantities of food. But those refinements can also be made verbally. A user who begins by saying: "For breakfast, I had a bowl of oatmeal, bananas, and a glass of orange juice" can then make the amendment,
"I had half a banana," and the system will update the data it displays about bananas while leaving the rest unchanged. According to MIT scientists, the apps that are currently available to help people try to log meals tend to be a little tedious, and therefore people are unable to keep up with them.
The researchers collected roughly 10,000 labelled meal descriptions and used machine-learning algorithms to find patterns in the syntactic relationships between words that would identify their functional roles.
