Other emotions relative to angry/happy base emotions In my layman's experience, I'm vaguely aware there are four base emotions: happy, sad, afraid/surprised, and angry/disgusted.1

Some background:  We're training an AI to learn the difference between happy voices and angry voices.  We've had some success, by showing it 200 angry audio clips, 200 happy audio clips, and 200 neutral.  It can now reasonably tell when we're talking pleasantly or confrontationally... but the accuracy could be better.

Our total training dataset is made up of these audio clips: Happy, angry, neutral, calm, sad, fearful, disgust, and surprised. I think we can be more accurate by including these emotions.  

But this is the problem:

Happy/angry/neutral span opposite ends of a spectrum; like binary.  It's easy to say:

Happy     1
Neutral   0
Angry    -1


That's the shape of the data we need to train a neural network to recognize 'Happy'. 

So the question would be, is there any 'right answer' on filling in these blanks?  I've given it my best guesses below, but I'm hoping for something more scientific....

Happy     1
Angry    -1
Neutral   0
Calm      X  (0.5?)
Sad       X  (-1?)
Fearful   X  (-0.5?)
Disgust   X  (-0.75?)
Surprised X  (0.75?)


 
1: http://www.theatlantic.com/health/archive/2014/02/new-research-says-there-are-only-four-emotions/283560/
As I mentioned in the comments, the tool we're using is pyAudioAnalysis.  The tool's author, Theodoros Giannakopoulos, also wrote an earlier paper "A dimensional approach to emotion recognition of speech from movies"

This "Emotion Wheel" from that paper appears to be exactly what I was looking for:


It's also worth mentioning, maybe, that this later paper seems to describe all the specific characteristics that pyAudioAnalysis analyzes: "signal energy, entropy of energy, zero  crossing  rate, spectral centroid, spectral flux, Mel Frequency Cepstral Coefficients, Chroma-based features, etc."