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Hume AI is an emotional intelligence platform that provides open-source models, curated speech datasets, and evaluation APIs for building voice AI with genuine emotional understanding. The platform draws on decades of scientific research covering more than 50 languages, 48 emotional dimensions, and over 600 voice descriptors.
Octave, the platform's LLM-powered text-to-speech system, generates expressive, natural-sounding audio that understands both the emotional and semantic context of the text it speaks. Developers can design custom voices through natural language descriptions, clone voices from short audio samples, and direct emotional delivery using acting instructions. Octave supports synthesis in 16 or more languages and delivers streaming audio with latency as low as 100 milliseconds, with export formats including MP3, WAV, OGG, FLAC, and PCM.
EVI, the Empathic Voice Interface, is a real-time speech-to-speech system combining emotion detection, speech recognition, and language model processing for natural, emotionally aware conversations. It supports interruptibility, pause and resume controls, chat history with emotion data, dynamic variable injection, and compatibility with external language models including Claude, GPT, Gemini, and others. SDKs are available for React, TypeScript, Python, .NET, and Swift.
The Expression Measurement API analyzes emotional signals across video, audio, images, and text, covering facial expressions, speech prosody, vocal bursts, and emotional language. Enterprise deployments include SOC 2 Type II certification, HIPAA compliance, custom SLAs, and dedicated support. A Human Feedback API enables teams to run scientifically grounded preference studies for voice model evaluation.
- Building voice AI assistants that detect and respond to users emotional states in real time
- Generating expressive text-to-speech audio with acting instructions and custom voice design
- Cloning voices from short audio samples for consistent brand audio production at scale
- Creating multilingual voice applications supporting native-quality speech across 16 or more languages
- Developing conversational AI agents with real-time emotion awareness and interruptibility features
- Running human evaluation studies to collect preference feedback on voice model quality
- Analyzing emotional signals in video, audio, image, and text with expression measurement APIs
- Integrating emotionally intelligent voice interfaces into healthcare applications using HIPAA-compliant infrastructure
- Producing curated speech training datasets with fine-grained emotional annotations across diverse domains
- Building real-time voice applications using low-latency streaming TTS with millisecond response times
- Adding emotional intelligence to existing language models through EVI external LLM compatibility
- Evaluating voice AI performance using scientifically grounded human feedback surveys and preference data
