PRODUCT DESIGN
Whispurr
Overview
Designing an app that utilizes Machine Learning AI, Generative AI and Augmented Reality to translate between cats and humans.
My Role
UX Research
UI Design
Design Systems
Prototyping
My Team
Gabriella Ramirez
Ibdita Hasib
Paola Rendón Márquez
Annie You
Duration
4 months
Tools
Figma
Illustrator
After Effects
Premiere Pro
The Problem 🤔
Cat adopters and owners often underestimate the importance of understanding their feline companions' personalities, needs, and communication cues.
The Solution 💡
To design an app that utilizes Machine Learning, Sound Recognition and Augmented Reality to act as a cat translator, so people can understand communication signs from cats.
Case Study Video
Initial Problem Discovery
With over 46.5 million U.S. households owning at least one cat, the demand for understanding feline behavior is significant. Many cat owners, especially new adopters, find it challenging to interpret their pets' subtle communication cues, which can lead to misunderstandings and affect the bond between owner and pet. Despite the popularity of cat ownership, existing tools and apps focus more on entertainment than on providing accurate behavioral insights, leaving a gap in the market for a truly effective solution.
Empathy Interviews
Through empathy interviews with a diverse group of cat owners, we uncovered common challenges they face in understanding their pets' behaviors. These insights highlighted the need for a more effective tool to help bridge the communication gap between cats and their owners.
Competitive Analysis
Existing cat translation apps focus on entertainment rather than accurate communication. Few apps provide unclear translations with low accuracy and inconsistent attitude illustrations, leaving users confused.
User Personas
So, how does Whispuur work?
The app utilizes machine learning AI that focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy.
Sound Recognition is an AI tool to analyze the sound of a mammal and classify the sound to an animal by interpreting the sound file’s frequencies.
Generative AI is used to produce cat sounds from the interpretation of human language, and vice versa.
FEATURE 1
Cat Translation
Through sound recognition, users can use their camera and/or microphone to understand their cat’s emotions and speech.
FEATURE 2
Cat Profiles
Machine Learning technology uses different profiles to keep track of individual cats’ behaviors and preferences separately and suggest interactive games through algorithms!
Takeaways
• Machine based learning can help people understand and communicate with certain animals.
• Generative AI is able to generate animal sounds so humans can accurately understand animal emotions.
Next Steps
• Further develop a a functional prototype and design system
• Improve UI Design
• Expand translation function to other pet animals in different app concepts.