The vertical axis shows activation level, the horizontal axis evaluation. A basic attraction of that arrangement is that it provides a way of describing emotional states which is more tractable than using words, but which can be translated into and out of verbal descriptions. Various techniques lead to that conclusion, including factor analysis, direct scaling, and others. Activation-evaluation space is a surprisingly powerful device, and it has been increasingly used in computationally oriented research. However, it has to be emphasised that representations of that kind depend on collapsing the structured, high-dimensional space of possible emotional states into a homogeneous space of two dimensions.
Extreme care is, thus, needed to ensure that collapsed representations are used consistently.
The information contained in the pair of output neurons should reflect as much as possible the information present in a subsymbolic way in the previous layer, with minimal loss of information. Speech consists of words spoken in a particular way. This section is concerned primarily with the information about emotion that resides in the way the words are spoken. There are relatively few systems, which approach the goal of recognising emotion automatically from a speech input. This section reviews key examples.