Speech Emotion Recognition (SER) through Machine Learning.
                     Speech Emotion Recognition (SER) 
through Machine Learning
INTRODUCTION
• Speech Emotion Recognition (SER) is the task of recognizing the emotional aspects 
of speech irrespective of the semantic contents.
• Automatic emotion recognition create efficient, real-time methods of detecting the 
emotions of phone users, call centre operators and customers.
Source: Medium
REPRESENTATION OF EMOTIONS
• Discrete Classification: 
– Classifying emotions in discrete labels like anger, happiness, boredom, etc.
• Dimensional Representation: 
– Representing emotions with dimensions such as Valence, Activation or Energy 
and Dominance.
Source: Medium
HOW DOES ML HELP IN EMOTION DETECTION?
• ML-based applications can detect emotions by learning body language traits such 
as facial features, speech features, bio signals, posture, body gestures/movement, 
etc.
•  ML apply this knowledge to the new set of data and information provided.
Source: Analytics Insight
FACIAL RECOGNITION
• ML-based facial recognition is a commonly used method for emotion detection. 
• It utilizes the fact that our facial features show significant changes with emotions. 
For example, when we are happy, our lips stretch upwards from both ends. 
Source: Acart Communications
SPEECH RECOGNITION
• Speech recognition for emotion detection involves speech feature extraction and 
voice activity detection.
• The process involves using ML for analyzing speech features to include tone, 
energy, pitch, formant frequency, etc. 
Source: Disruptive.Asia
BIOSIGNALS
• Emotion detection through bio signals is the process of analyzing biological 
changes occurring with emotion changes.
•  Bio signals include heart rate, temperature, pulse, respiration, perspiration, skin 
conductivity, electrical impulses in the muscles, and brain activity.
Source: Gulf News
BODY GESTURES AND MOVEMENTS
• Analyzing body movements and gestures also helps in emotion detection with the 
help of ML.
• Our body movements, posture, and gestures change significantly with changes in 
emotions.
Source: Interesting Engineering
MOTOR BEHAVIOURAL PATTERNS
• ML identifies the changes in behavioural patterns of a person with muscle tension, 
strength, coordination, and frequency also help define changes in the emotional 
state.
Source: Medium
FUTURE SCOPE
• This system can be employed in a variety of setups like Call Centre for complaints 
or marketing, in voice-based virtual assistants or chat bots, in linguistic research, 
etc.
Source: Commercial Integrator
CONCLUSION
• A combination of two or more of these methods can offer the best results 
in emotion detection through ML. 
Source: Analytics Insight