Hume AI Octave 2
Voice AI evaluation that measures 600+ dimensions of expression across 50+ languages — while Hume's TTS and EVI generation APIs wind down.
Buy Hume if you need to know why a voice agent fails when the transcript looks fine — VoiceEQ plus the Expression APIs and Human Feedback API are a genuinely hard-to-copy measurement layer, and the public Real World VoiceEQ and Voice Controllability leaderboards give you a benchmark starting point. Do not buy Hume for speech synthesis: TTS and EVI access ends November 13, 2026. For generation, look at ElevenLabs, Cartesia or Gemini 3.8 Flash TTS, which tops Hume's own leaderboard.
Verified 3d ago · liveness 82/100 · cite: rightaichoice.com/tools/hume-ai-octave-2
- Voice AI model teams comparing checkpoints across TTS, speech-to-speech, ASR and cascaded pipelines
- Agent teams that need to find where a deployed voice agent fails in real conversations
- Teams that want structured human-judged ratings without building a rater pipeline
- Enterprise contact center, healthcare, insurance and financial services deployments
- Anyone building on Hume's TTS or EVI generation APIs — access ends November 13, 2026
- Pre-launch teams with no conversation traffic for VoiceEQ to analyze
- Projects that just need a low-cost synthetic voice for narration
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Skip Hume if you are shopping for expressive speech synthesis — TTS and EVI access ends November 13, 2026 — or if you have no live conversation data yet for VoiceEQ to analyze.
The published plan figures are per-month with no billing period stated, so confirm whether you are committing monthly or annually before you budget.
Published tiers run from a $0 entry point through $3/mo, $14/mo (after a $7 first month), $70/mo, $200/mo and $500/mo to custom Enterprise with SOC 2 Type II, GDPR and HIPAA. That is cheap for a solo developer testing an agent and reasonable for a mid-size agent team; model labs doing checkpoint sweeps at volume will land in the $200–$500/mo band or Enterprise, where the comparison is a bespoke eval contract rather than a SaaS subscription.
In short
Hume AI Octave 2 — Voice AI evaluation that measures 600+ dimensions of expression across 50+ languages — while Hume's TTS and EVI generation APIs wind down. Best for Voice AI model teams comparing checkpoints across TTS, speech-to-speech, ASR and cascaded pipelines, Agent teams that need to find where a deployed voice agent fails in real conversations, Teams that want structured human-judged ratings without building a rater pipeline. Free to start; paid plans from $3/mo.
No head-to-head comparison for Hume AI Octave 2 yet — the alternatives below are the closest matches we list.
What's new in Hume AI Octave 2
Checked 3 days agoAcross the latest 5 updates: 1 feature update, 1 launch and 3 news mentions.
Hume launches Expression APIs for measuring 600+ dimensions of expression in 50+ languages
Expression APIs measure 600+ dimensions of expression across 50+ languages, extending scoring past the transcript to tone and facial cues in real time and on uploaded media.
Behind Hume's Expression Measurement Models for Face and Voice
Hume published the science and evaluation methodology behind its Expression API for real-time voice and facial expression measurement.
Hume sunsets TTS and EVI APIs, access ends November 13, 2026
Hume is sunsetting its TTS and EVI APIs. Access ends November 13, 2026 at 12:01 a.m. EST, and account data is deleted permanently after that.
Hume case study evaluates Google's multi-speaker TTS
Hume published an evaluation of Google's multi-speaker TTS, arguing private evaluations matter for conversational voice quality.
Gemini 3.8 Flash TTS tops Hume's Real-World VoiceEQ leaderboard
Hume extended its Real World VoiceEQ benchmark to voice controllability and replication; Google's Gemini 3.8 Flash TTS took the top spot.
What people actually say about Hume AI Octave 2 — is it worth it?
We scanned public community sources for Hume AI Octave 2 on Oct 11, 2026 and could not establish that the discussion we found is about this tool rather than something else sharing its name. Only 3 of the posts we fetched could be positively tied to Hume AI Octave 2. Rather than publish a sentiment score built on the wrong subject, we publish nothing here and re-run the scan.
Viability Score
How well maintained and how widely used is Hume AI Octave 2? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- VoiceEQ generates targeted evaluation suites from your real conversation data
- Stress-test voice systems and diagnose failures before release
- Validate fixes against defined success criteria before shipping
- Expression APIs score 600+ dimensions across 50+ languages
- Audio scoring across 414 expression and 190 voice-attribute names
- Video/facial scoring across 48 expression and 27 description names
- Realtime expression measurement over WebSocket for live audio and video
- Upload endpoints for recorded audio files and images
- Timing analysis: overlap percentages, gap duration, barge-in counts
- Background-noise SNR and accent coverage scoring per scenario
- Prism Pipeline turns unstructured audio into expression-rich training inputs
- Human Feedback API returns structured ratings from trained, vetted raters
- Real World VoiceEQ public leaderboards for models and agents
- Voice Controllability Leaderboard tests whether TTS follows directional prompts
- Python SDK (hume-expression-measurement) and Node.js SDK covering every endpoint
About Hume AI Octave 2
Hume AI now sells measurement, not synthesis. The VoiceEQ platform turns your real conversation data into targeted evaluation suites, stress-tests your voice system, diagnoses why it fails, and validates fixes before release. Underneath is a decade of emotion-science research: the Expression APIs score 600+ dimensions of expression across 50+ languages, covering tone, timing, interruption, barge-ins, background-noise SNR, accent coverage and conversational adaptation — the things a transcript cannot show. The infrastructure is modular. The Prism Pipeline turns unstructured audio into searchable, expression-rich inputs for training and evaluation. The Human Feedback API routes samples to trained, vetted raters so quality is judged by people rather than a model grading itself. Real World VoiceEQ publishes public leaderboards with a companion methodology report, including a Voice Controllability Leaderboard that tests whether TTS models actually follow directional prompts. Two buyers use it. Model teams compare checkpoints across TTS, speech-to-speech, ASR and cascaded pipelines and benchmark against alternatives. Agent teams pick a model, define use-case-specific quality by vertical (healthcare, insurance, financial services, customer support, travel, telecom) and validate realistic interactions. Hume claims 100M+ speech samples and adoption by five of seven leading AI labs. The material caveat: Hume's TTS and EVI APIs are being sunset, with access ending November 13, 2026 and account data deleted after that date.
Behind the Verdict
Hume made an unusual move and the site is honest about it: the company that shipped expressive TTS now sells the referee's chair. The measurement gap framing on the homepage — 'a task can succeed while the conversation fails' — is the actual product thesis, and it holds up against the detail. VoiceEQ's four steps (generate, stress-test, diagnose, validate) start from your conversation data and produce criteria lists, metric sets and experiment plans, which is the part most in-house eval harnesses never get to. The Expression APIs score audio out of 414 expression and 190 voice-attribute names, and video faces out of 48 expression and 27 description names, with upload endpoints for recorded media and WebSocket realtime endpoints for live calls — the realtime path is what makes live-call routing and monitoring plausible rather than batch-only. Python (hume-expression-measurement on PyPI) and Node.js SDKs cover every endpoint and ship microphone recording and WAV helpers, so a first script is not a research project. The Human Feedback API is the differentiator most competitors skip: trained, vetted raters scoring the qualities people actually experience, instead of an LLM judging its own output. Where it gets thin: Expression Measurement is documented as in limited release with access requested from the team, so plan for onboarding rather than instant self-serve keys. The pricing page returned generic marketing content in our capture, so treat the published tier figures as unverified against today's live page. And the big one — TTS and EVI access ends November 13, 2026, with account data deleted permanently after. If Octave 2 synthesis is why you are here, the road is closed; ElevenLabs, Cartesia and Gemini 3.8 Flash TTS are where to look, and Hume's own leaderboard will tell you which of them wins on your dimension. What survives and is worth paying for is the evidence loop.
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Real-world workflow fit
Concrete scenarios for the personas Hume AI Octave 2 actually fits — and what changes day-one when you adopt it.
You have a new speech-to-speech checkpoint and need to know if it beats the baseline on expression and turn-taking, not just transcript accuracy. You point VoiceEQ at your conversation logs, generate a suite, and compare baseline vs candidate.
Outcome: A criteria list and metric set you can hand to the team, plus per-dimension scores that show where the candidate regressed instead of a single pass/fail number.
Your support agent scores well on task completion but customers say it feels cold and talks over them. You run the conversations through expression measurement and look at overlap percentages, barge-in counts and timing gaps.
Outcome: You can point at the specific failure — say 24% overlap and 8 barge-ins in one scenario — and test a fix against the same criteria before it reaches production.
You want ratings from people rather than a model grading its own family. You route a sample through the Human Feedback API to trained, vetted raters.
Outcome: Structured human ratings you can compare against the automated scores, which is how the site itself frames the healthcare 0.84 auto versus 0.76 human gap.
Use Cases
- Find the real conversations where your voice agent breaks when the transcript looks fine
- Compare TTS, speech-to-speech, ASR and cascaded checkpoints against a baseline before release
- Benchmark your model against GPT-4o Realtime, Gemini Live, ElevenLabs v3 and Cartesia Sonic
- Define vertical-specific quality bars for a healthcare, contact center or financial services agent
- Route or monitor a live call using realtime expression measurement over WebSocket
- Ground an evaluation in human judgment with trained raters instead of a model grading itself
- Label a recorded audio dataset with expression and voice-attribute scores from a script
- Test whether a TTS model actually follows directional tone prompts
Models Under the Hood
as of 2026-10-16
Limitations
- Hume is sunsetting its TTS and EVI APIs: access ends November 13, 2026 at 12:01 a.m.
- EST and account data is permanently deleted after that date, so any synthesis pipeline you built on Octave or EVI needs replacing.
- The Expression Measurement API is documented as in limited release, with access requested from Hume's team rather than opened instantly.
- VoiceEQ needs real conversation data — with no traffic there is nothing to generate suites from.
- Our capture of the pricing page returned marketing content rather than a tier table, so the plan figures below could not be re-verified today.
- Emotion scores are probabilities per window of speech, which is a different thing from a correctness verdict; you still have to define success criteria.
as of 2026-10-19
Verification history
We have re-verified Hume AI Octave 2 20 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
Showing the 6 most recent of 20 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Hume AI Octave 2 tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free
$0/mo
Ideal for
A developer or solo builder testing an agent idea before committing budget, with 10,000 TTS characters and 5 minutes of EVI monthly.
What this tier adds
Free entry point: 1 concurrent connection and 15 requests per minute, with unlimited voice cloning.
Starter
$3/mo
Ideal for
A solo developer running light tests who needs a commercial license for voice conversion output.
What this tier adds
Adds voice conversion with a commercial license, 40 EVI minutes and 5 concurrent connections over Free.
Creator
$7/mo first month, $14/mo thereafter
Ideal for
An independent creator or small project producing steady sample volume who can absorb per-character overage.
What this tier adds
Jumps to 140,000 TTS characters and 200 EVI minutes, adds overage billing and lifts the rate limit to 75 requests per minute.
Pro
$70/mo
Ideal for
A working agent team at 1,000 minutes of usage a month that needs 10 concurrent connections for realistic testing.
What this tier adds
Ten times the Creator volume at 1,000,000 TTS characters, 1,200 EVI minutes, 10 connections and a lower $0.12 per 1,000 overage rate.
Scale
$200/mo
Ideal for
A mid-size team doing continuous evaluation across several models, needing seats and higher throughput.
What this tier adds
Adds 3 team seats, 20 concurrent connections, 150 requests per minute and 3,300,000 TTS characters.
Business
$500/mo
Ideal for
A company running evaluation as an ongoing production function with multiple stakeholders and support needs.
What this tier adds
Adds 5 team seats, Slack support, 30 connections, 225 requests per minute and the lowest listed overage rate at $0.05 per 1,000 characters.
Enterprise
Custom
Ideal for
Regulated deployments in healthcare, insurance or financial services that need compliance attestations and custom limits.
What this tier adds
Custom rate limits and concurrency, unlimited seats, SOC 2 Type II, GDPR and HIPAA, and custom integrations and evaluations.
Where the pricing makes sense
The company stage and team size where Hume AI Octave 2's pricing actually pencils out — and where peers do it cheaper.
Published tiers run from a $0 entry point through $3/mo, $14/mo (after a $7 first month), $70/mo, $200/mo and $500/mo to custom Enterprise with SOC 2 Type II, GDPR and HIPAA. That is cheap for a solo developer testing an agent and reasonable for a mid-size agent team; model labs doing checkpoint sweeps at volume will land in the $200–$500/mo band or Enterprise, where the comparison is a bespoke eval contract rather than a SaaS subscription.
Setup time & first value
How long it actually takes to get something useful out of Hume AI Octave 2 — broken out by persona, not the marketing-page minute.
A developer with API credentials can run a first audio upload with the Python or Node.js SDK in under an hour — the SDKs ship microphone and WAV helpers. Realistic setup is longer: Expression Measurement is in limited release, so request access first, then expect a day or two to define criteria and build a suite in VoiceEQ. Agent teams should budget a week to get conversation data in and pick
Switching to or from Hume AI Octave 2
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From a homegrown eval harness: Move your criteria into VoiceEQ's generate step and keep the Expression API scores as your metric set
- →From an LLM-as-judge setup: Route a sample through the Human Feedback API to replace model-graded scores with trained raters
- →From spreadsheet-based listening tests: Use the Prism Pipeline to turn your recorded audio into searchable, expression-rich inputs
- ↗To ElevenLabs: If you need synthesis, move TTS off Hume before access ends November 13, 2026
- ↗To Cartesia Sonic: An alternative TTS path named on Hume's own Real World VoiceEQ comparison
- ↗To Gemini 3.8 Flash TTS: Google's model took the top spot on Hume's Real-World VoiceEQ leaderboard in September 2026
Resources & Guides
Tutorials & Learning
Hume AIのOctave 2とEVI 4：共感音声AIの未来
AInewsCode
🎙️✨ 次世代の音声クローン？Hume AIのOctave 2をご覧ください。顔のないコンテンツクリエイターに最適です。
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YouTube returned 6 videos for “Hume AI Octave 2”, and we withheld 4: 4 did not mention Hume AI Octave 2. Showing the 2 we can prove are about Hume AI Octave 2.
Official links
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