Please use this identifier to cite or link to this item:
https://repository.iimb.ac.in/handle/2074/19556
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | De, Rahul | |
dc.contributor.author | Pujari, Maneesha | |
dc.contributor.author | Bodanki, Neel Kumar | |
dc.date.accessioned | 2021-06-11T14:44:37Z | - |
dc.date.available | 2021-06-11T14:44:37Z | - |
dc.date.issued | 2020 | |
dc.identifier.uri | https://repository.iimb.ac.in/handle/2074/19556 | - |
dc.description.abstract | Emotional AI or Affective Computing helps detect human emotions by using facial analysis, voice patterns, and deep learning to process them further and generate various degrees of the emotion present in the given output. According to Gartner, by 2022, personal devices will know more about a person’s emotional state than their own friends or family. The Emotional AI market is estimated to grow to $41billion by 2022, with existing players like Affectiva, Beyond Verbal, audEERING, and the big giants like Amazon, Google entering this space to understand their users’ emotions. As Emotional A is evolving over the years, it is shifting from deep EQ-guided experiences to detecting complex cognitive states like distraction and drowsiness. Affectiva is working in this space called the Human Perception AI, using real-world data, speech science, and computer vision, which helps autonomous vehicles. iii Lyrebird, a Canadian AI company, has created a system to mimic a human voice by analysing speech recognition and its corresponding AI transcripts | |
dc.publisher | Indian Institute of Management Bangalore | |
dc.relation.ispartofseries | PGP_CCS_P20_118 | |
dc.subject | Artificial intelligence | |
dc.subject | Emotions | |
dc.subject | Emotional AI | |
dc.subject | Affective computing | |
dc.title | Artificial intelligence in detecting emiotions | |
dc.type | CCS Project Report-PGP | |
dc.pages | 11p. | |
Appears in Collections: | 2020 |
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PGP_CCS_P20_118.pdf | 414.19 kB | Adobe PDF | View/Open Request a copy |
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