Page 46 - Banking Finance June 2024

ARTICLE

person's everyday activities, decision making, and the course Techniques for Developing Emotional AI
of their life are greatly influenced by their emotions.
Businesses must therefore be able to understand and A. Natural language processing (NLP)
The goal of the artificial intelligence field of natural
recognize human feelings or emotions to appropriately
language processing (NLP) is to give machines the capacity
position their goods or services. Herein lies the relevance of
to produce, comprehend, and interpret human language.
the concept of "emotional artificial intelligence" (Emotional
AI), an interdisciplinary field of study that investigates the Because NLP’s approaches make it possible to assess the
subtle emotional aspects of written and spoken text, they
extent to which robots are able to understand and respond
are crucial to the study of emotional AI. NLP analyzes tone,
to human emotions.
sentence structure, word choice, and other elements to help
Emotional AI, a branch of artificial intelligence recognizes AI systems understand and interpret the emotional
human emotions and reacts accordingly using advanced expressions expressed in written and spoken language.
machine learning techniques. Thanks to advances in
technology, machines are now easily able to recognize Important NLP approaches that help Emotional AI are
characteristics such as age, gender, race, personality, sentiment analysis and emotion classification. Sentiment
intentions, hobbies and mood. analysis divides text or voice into positive, negative, and
neutral attitudes. Emotion classification seeks to identify
Some of the basic techniques are face reading and speech specific emotions like happiness, rage, or sadness.
recognition. Emotional AI or artificial emotional intelligence
is the ability of machines to recognize, understand, quantify, These methodologies find applications in various tasks, such
and even mimic human emotions. Emotional AI is also as evaluating user emotions and providing relevant
referred to as human-centered artificial intelligence. responses by analyzing social media posts, customer
feedback, or conversational data.
EMOTIONAL A.I.
B. Computer vision and facial expression
Machines understand recognition
emotions or emotional Computer vision is crucial to the field of emotional AI as it
states with the help of
Deals with measuring enables robots to interpret and evaluate visual input such
human emotion, un- subtleties in the expres- as images and movies. AI systems can recognize emotions
sions on human faces.
derstanding stimuli, by using computer vision algorithms to detect and analyze
and giving back an ap- They measure stress or facial expressions. To recognize faces in images or videos,
propriate response anger with the help of facial features such as the mouth, nose and eyes are often
that will be he aptest sensors to understand removed. The recognized facial expressions are then
for the situation. the increased blood
pressure of the person classified using machine learning algorithms based on a
or changing tone of predefined set of emotions. The ability to respond in real
voice. time to users' emotions during system interactions gives AI
systems the potential to adapt flexibly.

The process of detect- This data is then
ing and recognizing mapped to the cues C. Machine learning algorithms with sentiment
emotions begins with that help us interpret analysis capabilities
machine learning. Data emotions in others. Identifying the sentiment or emotion communicated in
from passive sensors is speech or writing and classifying it as good, negative, or
gathered about the neutral is known as sentiment analysis. Because they may
physical state of the be trained to identify unique patterns and characteristics
person without any in- linked to emotions, machine learning algorithms are
put.
essential to this process.

40 | 2024 | JUNE | BANKING FINANCE