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Hume AI is an emotional intelligence lab focused on advancing voice AI through multimodal emotional understanding. Built by a team with decades of research experience, Hume AI provides open-source models, datasets, and evaluation APIs designed to embed emotional intelligence into voice models. It addresses the challenge of making voice AI more empathetic and human-like by analyzing emotions, prosody, and conversational dynamics across 50+ languages and 48 core emotions. The platform offers tools for human feedback collection, high-quality annotated speech datasets, and state-of-the-art voice AI models. Hume AI is ideal for developers, researchers, and companies working on voice assistants, conversational AI, and speech technologies who want to improve emotional accuracy and naturalness in their applications.
4.5/5
High-quality, nuanced, and scientifically grounded
Developer-focused with clean API design
To enhance voice AI systems with emotional intelligence and human-like expressiveness.
Accessible via RESTful APIs and open-source models, fitting into diverse voice AI workflows and platforms.
Freemium with enterprise options
Features with the highest value for users are highlighted here.
Multilingual emotional voice datasets
48 core emotion annotations
Human feedback API with vetted participants
RESTful API for evaluation studies
Open-source and closed-source voice models
Fine-grained prosody and intonation data
Domain-specific speech datasets
Fast human preference data turnaround
Voice AI Developers
AI Researchers
Customer Support Teams
Healthcare Tech
Gaming & Esports
Multilingual Product Teams
Speech Data Scientists
Startups
Enterprise AI Teams
Educators & Academics
Free
Pro
Weekly intelligence on AI strategy, operations, and market shifts. No noise. No narrative. Direct to your inbox.
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| Tool | Rating | Visits / mo | Global rank | Category rank | Engagement | Bounce | Top market | Starts at | Free tier | Integrations | Action |
|---|---|---|---|---|---|---|---|---|---|---|---|
 Hume AIAI Chatbots | 247.1K | #158,208 | #1,421 | 1m 19s3.5 pages | US(27%)#105,491 | $0 | 1 | View | |||
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