What is Vokaturi?

Vokaturi software stands as a prime example of advanced technology designed to identify emotions through vocal expressions. Developed and continuously improved by Paul Boersma, a professor at the University of Amsterdam and the mastermind behind the widely-used speech analysis tool Praat, its algorithms lead the industry in this specialized area. This innovative software can determine whether a speaker is experiencing happiness, sadness, fear, anger, or neutrality based solely on vocal indicators. The open-source iteration of Vokaturi demonstrates remarkable precision in identifying these five emotions, even when analyzing a speaker for the first time. On the other hand, the "plus" version boasts capabilities that can compete with those of a seasoned human listener. Developers are provided with the flexibility to smoothly incorporate Vokaturi into their applications, which enhances its adaptability for a range of purposes. Licensing options cater to different needs, offering either a complimentary open-source license or a premium one for additional features. Overall, Vokaturi not only serves as an accessible solution for emotion recognition in voice applications but also pushes the boundaries of what technology can achieve in understanding human emotions. Its ongoing development suggests a commitment to improving emotional intelligence in communication technologies.

Integrations

Offers API?:
Yes, Vokaturi provides an API
No integrations listed.

Screenshots and Video

Vokaturi Screenshot 1

Company Facts

Company Name:
Vokaturi
Date Founded:
2016
Company Website:
vokaturi.com

Product Details

Deployment
SaaS
Training Options
Documentation Hub
Support
Web-Based Support

Product Details

Target Company Sizes
Individual
1-10
11-50
51-200
201-500
501-1000
1001-5000
5001-10000
10001+
Target Organization Types
Mid Size Business
Small Business
Enterprise
Freelance
Nonprofit
Government
Startup
Supported Languages
English

Vokaturi Categories and Features

Emotion Recognition Software

Facial Emotions
Facial Expression Analysis
Machine Learning
Photo Emotions
Speech Emotions
Video Emotions
Written Text Emotions