Speech Emotion Recognition
To obtain a list of the top technology applications that detect emotion from speech, SER, in order to inform a technology application project that aims at detecting sentiment from speech.
- The top vendors in this industry include Apple (US), Google (US), Microsoft (US), IBM (US), Affectiva (US), Beyond Verbal (Israel), Noldus Information Technology (Netherlands), Tobii (Sweden), NEC Corporation (Japan), Sentiance (Belgium), nViso (Switzerland), Eyesight Technologies (Israel), Ayonix (Japan), Cognitec Systems (Germany), SightCorp (Netherlands), CrowdEmotion (UK), Kairos (US), Eyeris (US), and SkyBiometry (Lithuania), and iMotions (Denmark).
- The global market has penetrated various industries such as "medical emergency; marketing and advertisement; law enforcement, surveillance, and monitoring; entertainment and consumer electronics; robotics; and eLearning." These industries have had the most implementation, with medical emergency leading the pack.
Examples of SER Technology
- Audiary is an audio diary where patients of psychologists can assess daily progress. This makes it much easier for the patient who may have had to take notes by hand. By using audEERING's sensAI technology, it provides an analysis of the user's emotions.
- Callyser is a tool used in call centers to analyze speech. By using audEERING's sensAI technology, the tool detects the speakers' moods as well as the overall atmosphere of the conversation.
- SensAI Music is an innovative solution that analyzes the various aspects of a music track, such as tempo, meter, tune, vocals, genre, and the overall emotional setting of the song. This analysis is critical for those who handle large databases of music and need to plan set lists. Additionally, external factors such as lighting, avatars, and robots can be animated to be in sync with the track.
- Additional examples of Emotion Recognition APIs Emotient, Affectiva, EmoVu, Nviso, Kairos, Project Oxford by Microsoft, Fare Reader by Nodus, Sightcorp, SkyBiometry, Face++, Imotions, CrowdEmotions, among others.
Summary of our Early Findings
- Our initial one-hour research provides insights into the different vendors in this market, the industries implementing this technology, and examples of its application.
- Following our thorough research, we have provided different research paths that would add value to this research and provide a comprehensive report.
Proposed next steps:
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