Tell IBM Watson what you like in a Coffee - and then get a recommendation back
This is a very early version of an IBM Watson natural language classifier (NLC) integrated with speech to text and text to speech.
It is written in the R programming language.
CAUTION: The ground truth for the natural language classifier was a small subset of original Nespresso flavors of coffee flavors.
The user is prompted to describe the coffee flavors they most desire - then the system then responds with a recommendation of the Nespresso flavor most likely to fit their desires then the system asked him if they want to learn more about the coffee.
It's only about 10 of the dozens of flavors and recipes in the ground truth for NLC, but performs pretty well.
About this blog
This is an informal blog that explores tools, code and tricks that group members have developed to engage IBM Watson cognitive computing services - from the R Programming Language. Packages include RCURL to access Watson APIs - for services that include Natural Language Classifier and Speech to Text. THIS IS MY PERSONAL BLOG - it does not represent the views of my employer. Code is presented as 'use at your own risk' (it has lots of bugs)
Created: September 13, 2015English