May 29, 2023
No image
Completed
EdTech:Voice Recognition API Increases DAU by 19%
$25,000+
2-3 months
United Kingdom
2-5
Service categories
Service Lines
Artificial Intelligence
Domain focus
Education
Subcategories
Artificial Intelligence
Deep Learning
Challenge
The client, an EdTech startup teaches young children the alphabet via a mobile application. Through current teaching methods, the client is unsure of student progress and retention of knowledge taught in lessons. The clients want to leverage technology by “gamifying” the science of learning and tracking all progress.
The idea: codify dopamine into the user experience and make learning enjoyable and engaging, increasing time learning on the app and user retention.
The client, an EdTech startup teaches young children the alphabet via a mobile application. Through current teaching methods, the client is unsure of student progress and retention of knowledge taught in lessons. The clients want to leverage technology by “gamifying” the science of learning and tracking all progress.
The idea: codify dopamine into the user experience and make learning enjoyable and engaging, increasing time learning on the app and user retention.
Solution
Vacon proposed a speech-to-text API embedded inside the application that hears the student’s voice and scores accuracy of recognition and speed of recall. Positive affirmation is awarded through collectible accolades (badges) for the accomplishment of milestones. Passing the minimum set learning requirements unlocks the next lesson.
How it works:
Voice activity detection (VAC) was conducted on an audio dataset to extract words spoken from large audio files.
After extracting small audio we built a deep learning-based model in Pytorch and classified each audio into 10 classes (0 to 9).
Once achieving +95% test accuracy, a FlaskAPI was created and embedded into the mobile application.
Vacon proposed a speech-to-text API embedded inside the application that hears the student’s voice and scores accuracy of recognition and speed of recall. Positive affirmation is awarded through collectible accolades (badges) for the accomplishment of milestones. Passing the minimum set learning requirements unlocks the next lesson.
How it works:
Voice activity detection (VAC) was conducted on an audio dataset to extract words spoken from large audio files.
After extracting small audio we built a deep learning-based model in Pytorch and classified each audio into 10 classes (0 to 9).
Once achieving +95% test accuracy, a FlaskAPI was created and embedded into the mobile application.
Results
With its lightning-fast processing, the API transcribes and matches in a mere 50 milliseconds, ensuring a staggering accuracy of 95%.
Unlocked exponential growth with a notable 19% surge in Daily Average Users (DAU).
Witnessed a remarkable 12% boost in retention rate, nurturing long-term customer loyalty.
Immersed users in captivating experiences with an impressive 32% increase in average session length.
Harness the power of our API for unparalleled success and elevated user engagement!
With its lightning-fast processing, the API transcribes and matches in a mere 50 milliseconds, ensuring a staggering accuracy of 95%.
Unlocked exponential growth with a notable 19% surge in Daily Average Users (DAU).
Witnessed a remarkable 12% boost in retention rate, nurturing long-term customer loyalty.
Immersed users in captivating experiences with an impressive 32% increase in average session length.
Harness the power of our API for unparalleled success and elevated user engagement!