Hume AI

Hume AI provides VoiceEQ evaluation, expression-measurement APIs and human-rated feedback that help AI labs and enterprises test and improve how voice models and agents perform with real people.

What is Hume AI?

Hume AI builds tools for measuring and improving how voice AI performs with real people. Its focus today is evaluation infrastructure: rather than only checking whether a voice agent completed a task, Hume looks at how the conversation felt, including tone, timing, interruptions, accents, background noise and emotional expression.

The company draws on more than ten years of emotion science research and says its tools are used by five of seven leading AI labs. Its customers are AI labs building speech models and enterprises deploying voice agents in areas such as healthcare, contact centres, financial services and retail. Hume also develops its own voice models, including the Octave text-to-speech system.

Key Features of Hume AI

VoiceEQ evaluation platform

VoiceEQ analyses your conversation data to identify use cases, then generates targeted test cases, success criteria and metrics. It supports stress-testing, diagnosing failures and validating fixes in one loop.

Real-World VoiceEQ benchmark

A public leaderboard compares speech-to-speech and text-to-speech models on dimensions such as expression, naturalness, turn-taking, contextual fit and transcript accuracy, with a published methodology.

Expression APIs

These APIs score vocal, facial and language expression, covering more than 600 dimensions in 50+ languages. Audio can be streamed for scores that update during a conversation turn, or analysed clip by clip with timestamped segments.

Human Feedback API

Evaluations can be grounded in human judgment through structured ratings from trained, vetted raters, useful where automated metrics miss how people actually experience a voice.

Prism Pipeline

Prism turns unstructured audio into searchable data enriched with tone, timing and emphasis, ready for evaluation or model training. Hume describes these as the same research systems it built to develop its own voice models, now offered through APIs or inside your own environment.

Hume AI Pricing

Hume does not publish self-serve prices for its current platform; the former pricing URL now leads to the homepage, and access is arranged by requesting access or talking to the team.

Prices checked on October 27, 2026; check the official pricing page for current plans.

Who Should Use Hume AI?

• AI labs developing TTS, speech-to-speech or ASR models.
• Enterprises choosing and tuning voice agents for customer conversations.
• Product teams adding emotion-aware behaviour to apps or robots.
• Researchers in market research, coaching or accessibility who analyse vocal expression.
• Hiring and sales-coaching teams that review recorded conversations for moments worth a closer look.

Is Hume AI Worth It?

For organisations where voice quality directly affects outcomes, Hume offers something few vendors do: a structured way to measure how a voice system feels to users, backed by human ratings and long-running emotion research. The public benchmark is also a useful free reference when comparing models.

It is not a consumer tool. There is no published pricing, access requires contacting the company, and the platform assumes you have conversation data and an engineering team to act on the results. Emotion and expression scores are probabilistic estimates rather than certainties, and analysing people's voices or faces raises consent and privacy questions you should address before deployment. Enterprise voice teams should evaluate it; individuals will find little to use directly.