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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

A technology-focused platform designed for consumer insights teams enables the mapping of insights across various media, digital, and shopper interactions, facilitating the creation of emotionally resonant customer experiences while optimizing the customer journey to enhance conversion rates. Additionally, it provides valuable insights into emotion, attention, engagement, and visibility. For UX teams, it offers a usability testing and analytics platform that evaluates attention, engagement, and emotional responses throughout user journeys, allowing for the testing of prototypes, mockups, websites, applications, and chatbots. This platform helps in pinpointing crucial UI elements that attract customer attention, ensuring the delivery of emotionally optimized user experiences that drive higher conversion rates. Furthermore, it leverages Emotion Insights to craft exceptional customer experiences, utilizing Facial Coding APIs to assess emotional responses at scale through single face emotion recognition, in-the-wild multi-face emotion recognition, and recorded video emotion analysis. The platform is capable of testing stimuli across diverse modes and channels such as videos, print advertisements, planograms, package designs, websites, applications, and chatbots, ensuring comprehensive insights into consumer behavior and emotional engagement. This multifaceted approach empowers brands to refine their strategies and create impactful interactions with their audience.

Description

Vokaturi software exemplifies cutting-edge technology in recognizing emotions through vocal cues. Crafted and continually refined by Paul Boersma, a professor at the University of Amsterdam and the chief creator of the renowned speech analysis tool Praat, its algorithms are at the forefront of this field. This innovative software can accurately assess whether a speaker is feeling happy, sad, fearful, angry, or neutral based solely on their voice. The open-source variant of Vokaturi provides impressive accuracy in distinguishing these five emotions, even when encountering a speaker for the first time. In contrast, the "plus" version offers performance that rivals that of an experienced human listener. Developers have the option to seamlessly integrate Vokaturi into their applications, making it a versatile tool for various uses. Licensing options are flexible, allowing users to select either a free open-source license or a paid one for enhanced features. Overall, Vokaturi presents an accessible yet powerful solution for emotion recognition in voice applications.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

No details available.

Integrations

No details available.

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Affect Lab

Founded

2016

Country

India

Website

affectlab.io

Vendor Details

Company Name

Vokaturi

Founded

2016

Website

vokaturi.com

Product Features

Emotion Recognition

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

Usability Testing

A/B Testing
Annotations
Audience Targeting
Heatmaps
Impression Testing
Mobile Testing
Moderated Usability Testing
Prototype Testing
Quantitative Metrics
Remote User Testing
Reporting / Analytics
Surveys and Feeback
Video Recording / Transcription

Product Features

Emotion Recognition

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

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Alternatives

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