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Emotion Detection and Recognition Industry Share, Trend, Growth, Size, Forecast 2028

The past, present & future of Emotion Detection and Recognition

11th January 2023 by Aditya Jain | IT & Telecom

Emotion Detection and Recognition

Brief Outlook

Emotion Detection and Recognition is the speech-based emotion detection device used to analyze human emotional states through Facial Recognition, Gesture Recognition, Speech Analytics, and Text-Based Recognition. The detection and recognition of human emotional states are analyzed by the use of technological capabilities, such as IoT, AI, ML, and deep learning technologies. The methodology or invention of emotion detection and recognition devices are used in the various work area, they are ready to determine the work stress in the workplace for more productive working styles, to detect candidates’ reactions during the interview so that interviewer can analyze the behavior and optimize the structure for future. Emotion Detection and Recognition are also used in the area of Law enforcement, surveillance, and monitoring.

Branches of Emotion Detection and Recognition are:

  • Facial Emotion Recognition – To detect emotions through facial expression, which is done by capturing images or videos through surveillance cameras or personal devices and sending them to FER algorithms. FER algorithms are the systems that use computers to analyze human expressions and emotional patterns through IoT, AI, ML, and deep learning technologies. First, it detects the face from the picture or the video, then second, they detect facial expression, your nose or eyebrows, etc. Third, they classify your emotional state, i.e., anger, disgust, fear, joy, sadness, and surprise. The use of facial emotion recognition interprets customer behavior in healthcare, employment, education, public safety, crime detection, and others.
  • Gesture Recognition – To detect emotions through gestures and body movements. It is used to analyze humans' cognitive activity, personality, intention, and psychological state. It is done by a camera and the motion sensor to interpret results. If we can easily punch into the screen of touch screen phone if we want to look closely at something. Virtual reality and Augmented reality can be used to detect gestures and body movement. It can be used in the area of public health, Health Diagnostics, and Security.
  • Speech Analytics – To detect emotion through speech emotion detection. The uses of Speech Analytics are in marketing, healthcare, customer satisfaction, gaming experience improvement, social media analysis, stress monitoring, and others. First, we have to do data processing with audio data from humans with emotions, with the use of python, MATLAB, or others we extract the emotion labels from the speech. Second, we have to perform Acoustic Feature Extraction in which we convert audio into a digital representation of waves. Through particular demand, we can convert sound into numbers or data. Third, we are doing Filtering and Splitting the Data, we bifurcate it in a histogram with the percentage of data of each class emotion of surprise, calm or sad, etc. Fourth, we are done with Modeling and Scoring, in which we create a matrix which results shows the numeric percentage data for different emotions. How data with one emotion can be altered with another one. At last, we predict how a speaker uses different emotions with different alterations in a speech. The potential market for speech analytics is high in customer care services, BPO, and others.
  • Text-Based Recognition – To detect emotions through Text-Based Emotion Detection. When a person writes down their thoughts or certain words in text form, the emotions in each expression were embedded to understand the nature of writing. The formula for emotion from text is:

r: A×T →E

A stands for the author, T stands for text, E stands for emotion, and r is the function that expresses the emotion of the author from the text.

First, it detects text, molds it into a simpler form, and identifies the emotion word. In the next step, we will identify the intensity of emotion and check the negation in the sentence. At last, we interpret the emotion of the text of the author and what they are tried to express in their writings.

Gadgets use in Emotion Detection and Recognition!

  • Apple – Apple launched Siri, through which you can regulate your gadgets, it can regulate your mood-tracking app based on your emotions or behavior.

  • Google – Google Cloud Vision API use to detect your face, landmarks, and objects to determine your emotions through vision API. Use machine learning models to define your image emotion with inbuilt millions of predefined emotion categories.
  • Intel – Intel builds Entropik Emotion Detection and Analytics, used to recognize consumer behavior and responses. With the use of AI models, it can capture all the parameters of emotion categories. It is highly used by companies to understand consumer behavior.
  • IBM – IBM Watson uses to detect textual emotion detection on the Watson developer cloud. With some new enhancements, they improve their features with new vocabulary coverage, feature selection, classifiers, and lexicon/word level.

Market Trends for Emotion Detection and Recognition

The market size for Emotion Detection and Recognition is at 13% of the CAGR of 45 billion, by 2028. Innovations in the technologies take Emotion Detection and Recognition to an advanced level. The use of these dynamic technologies in the various areas of call-center to understand the emotions of customers, in children’s speech grooming diagnosed with autism. The highest market for the Emotion Detection and Recognition market in North America. The market for smart watches, fitness bands and smart glasses has witnessed a growth of 80% in sales in the last 4 years. Due to the mature market and significant Research and Development department of America, the development of the Emotion Detection and Recognition market is high. The Automotive industry is the highest demanding sector in the Emotion Detection and Recognition market. It can help to detect the mental state of the driver. As per the segment growth, the facial expression recognition segment shares the largest market. It is highly used in the emotional detection of an individual’s cognitive state, intention, personality, and psychology and generates responses. Use of smartphones or cameras to capture an image and send it to FER algorithms to interpret the emotional state.

Which Region dominates in the Emotion Detection and Recognition Market?

North America is the dominating region by 2021 and is expected to dominate further. Due to the largest markets of the United States or Canada, the growth of the Emotion Detection and Recognition market is high. The companies like IBM, Microsoft, Apple, Google, and Intel are the major vendors to grow the ED/ER business effectively. COVID affects the Emotion Detection and Recognition market harshly, the market is witnessing to experience a sharp decline in 2020. Emotion Detection is the method used to analyze human emotion through the face, and gesture recognition, but the pandemic compelled humans to cover their faces through masks or glasses to avoid social interaction and obtain obstacles in facial recognition.

Public and Social Acceptance

The market for smart watches, fitness bands and smart glasses has witnessed a growth of 80% in sales in the last 4 years. These technologies are embedded with high innovations including biological sensors to monitor heartbeat and temperature, along with other components, such as microphones and cameras to capture that can easily capture human emotions, gestures, body postures, tone of voice, and facial expressions. People are more attracted to these new features that can be easily handled on their wrists. These wearable devices are the major factor in the growth of the Emotion Detection and Recognition market among humans.  Whereas, the higher cost in the manufacturing of Emotion Detection and Recognition market can restrict its use of it in daily life.

There was a time when people used to think that they wish if they could understand the mind/ inner thoughts of the person, but we were unable to do that. Now, technology has gone so far that we can interpret the mental state of a person even without telling us anything. Emotion detection and recognition through Machine Learning or Artificial Intelligence, we can easily interpret the mental state of others, and this will attract individuals to use it more significantly.

Recent Updates in the Development Area

  • On the 17th of April 2022, Intel develops an emotion AI method teaching tool software to detect students’ emotions. When the education platform comes to virtual mode than it is difficult for teachers to understand students’ emotions from a virtual meeting class. Intel and Classroom technologies come together to develop a classroom software that is integrated via Zoom as “Class”, providing the emotional status of the child.

  • On the 12th of November, 2021 Kyndryl announced a partnership with Microsoft, for cloud-based services, modernizing applications and processes, helping with the critical workload, and modernity. The partnership helps to take Emotion Detection and Recognition technologies to people’s reach.
  • On the 28th of July, 2020, NEC Corporation and Realeyes signed a Memorandum of Understanding to come together to develop emotion analysis solutions for humans. NEC Corporation, the biometric authentication, and video analytics technologies professional company, and the Realeyes, a computer vision and emotion Artificial Intelligence (AI) technology professional company, both jointly deliver their combined technologies and services to develop multiple emotion detection and recognition methods to enhance the user experience.
  • On the 6th of June, 2019, Realeyes partnership with Intralink to invest $ 12.4 million to expand their business in APAC EMEA. The company invests to develop Emotion AI to help brands like AT&T, Mars, Hershey’s, and Coca-Cola, to monitor human emotion through written survey responses, photos or GIFs, and videos.

Conclusion

Emotional Detection and Recognition are used to monitor human emotional states through Facial Recognition, Gesture Recognition, Speech Analytics, and Text-Based Recognition. Upcoming new technologies and innovations rapidly develop the Emotional Detection and Recognition market. The scope of Emotional Detection and Recognition devices are in various industrial sectors, they are used to analyze the emotions of customers through the pitch tone, used in the healthcare sector to interpret heart rate, pulse, and body temperature. Companies use written surveys, ratings, or comment sections to understand the customer’s reactions, instead of this the use of emotion detection and recognition is the right choice to replace all the boring methods to monitor consumers’ reactions. The new accelerating innovations, and developing Research and Development department generates the new methods to enhance the experience of media, entertainment, education, healthcare, and communication verticals across the world. But the only restrain in the development of the Emotion Detection and Recognition market is the high manufacturing cost of their devices. The Research and development department continues to develop products that are cheaper in rate to increase the reach of their products. Besides, any challenges or restrains the demand for the Emotion Detection & Recognition method to monitor human emotional state is increasing and reached 45 billion, by 2028.

Aditya Jain

Research Analyst

Aditya Jain is the research analyst at Delvens. He focuses on researching emerging trends, data, and analytics globally. His core responsibilities include conducting extensive interviews with market experts to diagnose the challenges and highlight upcoming opportunities. He aims at providing the best market insights where ever required and aspires to as many market leaders with the best of his valuable information.

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