Hume provides the AI toolkit to measure, understand, and improve how technology affects human emotion. Our algorithms understand nuanced speech prosody, vocal bursts, facial expression, and tone of language—which, integrated into large language models, will determine how people experience the future of AI. Our APIs can process video, audio, images, or text and can be integrated with LLMs to build better healthcare solutions, digital assistants, communication tools, and more.
- Hume AI Intro: The New Science of Expression https://hume.ai/video/
- Fundamental Advances in Understanding Nonverbal Behavior | Keynote by Alan Cowen | ICML 2022 https://youtu.be/4-EEhdqETJY
- Our interactive expression model maps for the voice, face, and language: https://hume.ai/products/#models
Example code we'll walk through in our API workshop that integrates expression understanding and LLMs will be Humechat
Navigate to bit.ly/calhacks_hume to sign up.
Developer Documentation is located at dev.hume.ai
You can reach us in our CalHack Hume Slack Channel - CalHack Hume Slack Channel
TBD
The projects in this repo are for you to use as samples to build your project.
NodeJS
Provides a sample on how to use Hume AI Streaming API with your webcam and mic.
Python
Provides a sample on how to use OpenAPI with Hume AI. It will provide a sample on how to stringify Hume API expression predictions with OpenAPI.
Python
Expressions2Text tool takes a (48,1) array of emotion scores and transforms it into human understandable text, which can then be further transformed into a language embedding.
- Health & Wellness: Clinical diagnosis (e.g., depression, autism); patient monitoring, therapy
- AI Research/Services: The next generation of search, recommendation, and content generation
- Social Networks: Toxicity detection; health/well-being monitoring; relationship compatibility
- Call Center Analytics: Call triaging (e.g., frustration); emergency detection (e.g., pain); training
- Embedded Devices: Social robots; AI dashcams; warehouse safety
- Brand/Financial Analysis: Sentiment analysis for market forecasting and brand sentiment research
- Creative Tools: Character animation; content generation, editing, and curation
- Digital Assistants: Conversational AI (e.g., backchanneling); optimization (e.g., ↓ frustration)
- UX/CX Research: Sentiment analysis of user interviews and tests
- Gaming & XR: Animation; virtual characters; moderation (e.g., bullying); optimization
- Education/Coaching: Focus/boredom detection; student well-being; leadership coaching
- Sales/Meeting Analytics: Sales rep coaching; analyzing customer engagement and sentiment