humans show a great deal of variability in their abilities to recognize emotion. a key point to keep in mind when learning about automated emotion recognition is that there are several sources of "ground truth," or truth about what the real emotion is. suppose we are trying to recognize the emotions of alex. one source is "what would most people say that alex is feeling?" in this case, the 'truth' may not correspond to what alex feels, but may correspond to what most people would say it looks like alex feels. for example, alex may actually feel sad, but he puts on a big smile and then most people say he looks happy. if an automated method achieves the same results as a group of observers it may be considered accurate, even if it does not actually measure what alex truly feels. another source of 'truth' is to ask alex what he truly feels. this works if alex has a good sense of his internal state, and wants to tell you what it is, and is capable of putting it accurately into words or a number. however, some people are alexithymic and do not have a good sense of their internal feelings, or they are not able to communicate them accurately with words and numbers. in general, getting to the truth of what emotion is actually present can take some work, can vary depending on the criteria that are selected, and will usually involve maintaining some level of uncertainty.