Measure what words can't capture
A comprehensive suite of models for analyzing human expression across face and voice. Detect nuanced emotions with scientific precision using the same methods trusted by researchers worldwide.
Built on Science
Decades of research, one platform
#1
in naturalness and expressivity
600+
tagsof emotions and voice characteristics detected
250
msspeech LLM latency
Model Suite
Seven specialized models, one unified API
Each model is purpose-built for a specific aspect of expression analysis. Use them individually or combine them for comprehensive multimodal understanding.
Speech Prosody
Analyze rhythm, stress, and intonation to understand emotional undertones.
Vocal Expression
Detect emotions from voice timbre, resonance, and vocal quality.
Vocal Bursts
Recognize laughter, sighs, gasps, and other non-verbal vocalizations.
FACS 2.0
Industry-standard Facial Action Coding System for precise AU detection.
Dynamic Reaction
Track how expressions change over time in response to stimuli.
Facial Expression
Comprehensive emotion recognition across cultures and lighting conditions.
Language
Analyze text for emotional expression, sentiment, and content safety.
Scientific Foundation
Built on decades of research
Our models are grounded in peer-reviewed emotion science, developed in collaboration with leading researchers in psychology, affective computing, and machine learning.
Peer-reviewed methods
Built on 53+ publications in affective science and validated by independent researchers.
Neuroscience-informed
Models designed around how the brain actually processes and expresses emotion.
Validated accuracy
Benchmarked against gold-standard datasets with documented performance metrics.
Continuous updates
Regularly refined with new research findings and expanded training data.
For Developers
Simple API, powerful results
Send images, audio, or video to our API and receive structured emotion predictions in milliseconds. Full SDK support for Python, TypeScript, and more.
from hume.expression_measurement.batch import Face, Models
client = HumeClient(api_key="YOUR_API_KEY")
job_id = client.expression_measurement.batch.start_inference_job(
models=Models(face=Face()),
urls=["https://example.com/media.mp4"],
)
predictions = client.expression_measurement.batch.get_job_predictions(
id=job_id
)
Case Studies
See what others are building
Niantic Spatial × Hume AI: Creating Interactive & Spatially Aware AI Companions
In partnership with Snap Inc. (hardware) and Hume AI (voice), Niantic Spatial has developed location-aware companions for Spectacles, blending Snap Inc.’s AR glasses, Niantic Spatial’s Large Geospatial Model, and Hume’s Empathic Voice Interface (EVI) for natural, emotionally intelligent conversation. Niantic Spatial, the team pioneering AI that understands the physical world, is showcasing a compelling glimpse of what can happen when spatial intelligence and augmented reality meet.
GAF Powers Professional Training with Hume’s Text-to-Speech
To support their extensive training programs and marketing initiatives, GAF leverages Hume's text-to-speech technology to make internal training videos and marketing voiceovers. Our partnership addresses several key needs: Professional training content: Delivering consistent, high-quality audio for thousands of contractors and employees. Marketing collateral: Producing engaging voiceovers for promotional content and product demonstrations. Scalable production: Generating content without the logistics and cost of traditional voice recording. Hume's voice design also proved ideal for GAF. The platform's natural, expressive voices maintain the authoritative yet approachable tone that GAF needs to communicate with contractors, retailers, and customers. Unlike synthetic voices that can sound robotic or overly casual, Hume's TTS technology delivers the polished, trustworthy quality expected from an industry leader.
Hume AI powers conversational learning with Coconote
While traditional note-taking apps require students to manually scroll and search through content, Coconote is creating interactive study experiences through conversational AI. Coconote’s voice chat feature, powered by Hume's EVI, helps users transform static notes into dynamic conversations. Students can: Ask natural questions about their lecture content Receive contextual explanations referencing specific notes, and Engage in quiz-style conversations for active learning—all through natural voice interaction.
FAQ
Frequently asked questions
Ready to measure expression?
Start analyzing emotions from face and voice with our suite of research-grade models. Free tier available.