Afective computing and emotions in AI

AKAOKA BADSSI SaraEmpath Inc.12/07/2017

Introduction

AI and technology more and more vital in life and society

Almost every domain field relies on it: medical, entertainment..

computers not only actors in technology but also in society

How to make more sociable machines? Many researchers agree that emotions are part of the answer

Emotional intelligence

In social interactions, emotions carry pieces of information: express one's intentions, interests in the conversation and state of mind

understanding those emotions can improve the interaction between the parties

Isen: emotions can have an infuence on the thinking and reasoningsome tasks are more suitable for some emotions

greeting happiness, comfort compassion=> exploit and optimize the abilities of the interlocutor by infuencing their emotion

Not only social context: humans need emotions for their survival and adaptation to societyEx: fear of dangerous situations makes people avoid the danger

understanding the emotions, their origin and consequences=

emotional intelligence

Tis intelligence allows an individual to make beter decisions for their social and professional integration.

Afective computing

Domain of human-machine interaction

Goal: expand the human emotional intelligence to the machines overcome the emotional and social gap between human and computers

create socially intelligent machines capable to respond approprietaly according to the situation and the interlocutor

Afective computing: Discrete approach

Lots of theories based on both discrete and continuous approaches positive/negative emotions, primary/secondary...

Discrete theory: Paul Ekman

- 6 basic emotions: happiness, anger, fear, neutral, sadness and disgust- the rest of the emotions can be computed as a combination of those basic ones

Strong points: universality of the emotion recognition a basis of a small number of emotions

Weak points: more negative emotions than positive multiple expressions for one emotion

Afective computing: Continuous approach

Russell's theory:

All of the emotions can be described with only arousal and valence

Strong point: only two dimensions, theoritically one could extract all of the emotions with this

Weak point: how to measure those parameters? Which parameters correspond to arousal? And intensity?

Empath's challenges

Goal: recognize emotions regardless of the language

Strong points:● A lot of researches and theories about affective computing, not much practice● a lot of studies been done in speech processing, and we can communicate

with machines

Challenges:● Affective computing mostly done on facial expression

The universality that Ekman proved is for facial expression only● The speech processing that we know is based on words, not emotions. We

know which parts of the spectogram, of the vocal properties take into account for speech synthesis or recognition, but not emotions

Challenge: Combine both speech and emotions

Empath's approachPre-processing the data:- pitch- intensity- speech rate

However, some more or less major obstacles come in the way:- how to extract those information accuratly and quickly (real-time)- choice of the model: Random Forest, NN, LSTM...- still lots of debates about the accuracy of these findings- individual characteristics (tone, pitch, natural intensity...)- context and culture

Need of data: 4 emotions, 5 expressions each, 2 genders, 3 types of voices (child, adult, senior), 1 culture: 240000 samples needed

one solution: adding prior information

What's next?

“Soon enough it was discovered that it was difficult to find specific voice cues that could be used as reliable indicators of vocal expressions.Whereas listeners seem to be accurate in decoding emotions from voice cues, scientists have been unable to identify a set of cues that reliably discriminate among emotions.” (Petri Laukka – Vocal Expression of Emotion. Descrete-emotions and Dimensional Accounts – 2004)

Is it a lost cause then?

Not one right answer, but rather a combination of answers, provide accurate additional information.Emotions don't carry the entire message and information, they carry another type of information, different from the one carried in speech and words.

Thank you for your attention!