STEP 01
WHAT WE SOURCE
Recruit verified speakers, capture scenario audio.
Native speakers, regional accents, real environments. Every recording is consented, attributed, and tied to speaker metadata before it enters the pipeline.
→AI LABS · VOICE · LICENSED HUMAN SPEECH
Train better voice models with real human speech.
AuraOne helps voice AI teams source licensed multilingual speech data, evaluate model quality, and improve voice performance across languages, accents, emotion, and real-world conversations.
LICENSED SPEECH
47 accents
Human recordings with consent, transcripts, labels, and delivery metadata across the languages your model is missing.
HUMAN EVALUATION
14 dimensions
Naturalness, pronunciation, latency, turn-taking, safety, and release readiness — reviewed by trained voice raters.
REGRESSION COVERAGE
451 test sets
Reusable banks that follow voices, languages, agent behaviors, dubbing pipelines, and safety policies release after release.
WHY IT EXISTS
Voice models do not fail in perfect studio conditions.
They fail in cars and kitchens. In accents the demo never tested. In the half-second pause before someone interrupts. AuraOne closes those gaps with licensed voice data, human evaluation, and regression banks that follow every model release.
FAILS IN
Accents
regional pronunciation, rhythm, and vocabulary
FAILS IN
Noisy rooms
cars, homes, offices, public spaces, cheap mics
FAILS IN
Emotion
stress, hesitation, excitement, anger, comfort
FAILS IN
Mixed languages
code-switching and local phrasing
FAILS IN
Real conversations
interruptions, backchannels, silence, repairs
HOW IT WORKS
Three steps. From recording to release.
Source the speech. Standardize the review. Sign the release packet. Every recording carries its reviewer, its consent, and its quality score forward.
STEP 02
WHAT WE REVIEW
Transcripts, labels, and audio quality, reviewed by humans.
Trained reviewers verify transcripts, pronunciation, emotion, accent fit, and quality. Every label carries the reviewer who signed for it.
→STEP 03
WHAT WE SIGN
Model-ready files with usage rights attached.
Clean metadata, QA reports, consent documentation, and delivery manifests — packaged for training, evaluation, or release testing.
BUILT FOR
Every major voice and audio model workflow.
Whether you are improving pronunciation, expanding language coverage, testing emotional delivery, or evaluating a new realtime model, the same data and evaluation pipeline carries the work forward.
MODEL · 01
Text-to-speech models
MODEL · 02
Speech-to-text models
MODEL · 03
Speech-to-speech models
MODEL · 04
Voice cloning systems
MODEL · 05
Dubbing and localization models
MODEL · 06
Real-time voice agents
MODEL · 07
Multimodal audio models
MODEL · 08
Voice safety and abuse detection systems
ACCENT AND LANGUAGE COVERAGE
Cover the accents and languages your model is missing.
Most voice models sound impressive in English demos. The real challenge is global coverage. AuraOne can shape language programs around your model gaps, target markets, or release roadmap.
ENG · COVERAGE
English accents
US, Canadian, British, Australian, Indian English, Singaporean English, Nigerian English, Southern US, New York, California, Irish, Scottish.
ESP · COVERAGE
Spanish variants
Mexican, Colombian, Argentinian, Chilean, Castilian, Caribbean, US Hispanic.
IND · COVERAGE
Indian languages and accents
Hindi, Punjabi, Gujarati, Tamil, Telugu, Bengali, Malayalam, Marathi, Hinglish, Indian English.
ARA · COVERAGE
Arabic variants
Gulf, Egyptian, Levantine, Moroccan, Modern Standard Arabic.
ASN · COVERAGE
Asian languages
Mandarin, Cantonese, Japanese, Korean, Tagalog, Vietnamese, Indonesian, Thai.
EUR · COVERAGE
European languages
French, German, Italian, Portuguese, Dutch, Polish, Turkish.
CONVERSATIONAL SPEECH
Real conversations, not just read-aloud audio.
Modern voice models need to handle not only what people say, but how they actually speak.
SCENARIO LAYER
Dialogue shape
Two-person exchanges, long-form companion dialogue, coaching, tutoring, support, and task-oriented speech.
Environment shape
Home, car, office, public space, device, microphone, and noise context stay attached to the audio.
↳ USE CASES · LIVE
- 01Two-person conversations
- 02Customer support calls
- 03Sales and service roleplays
- 04Tutoring and coaching scenarios
- 05Healthcare intake simulations
- 06Financial and insurance conversations
- 07Travel and hospitality interactions
- 08Noisy home, car, office, and public environments
- 09Emotional conversations
- 10Code-switching and mixed-language speech
- 11Long-form voice companion dialogue
WORKFLOW · THREE STAGES
The walkthrough your team runs.
Data, evaluation, and safety move through one pipeline. Each stage carries its own evidence and its own reviewer. The record travels with the work.
STAGE · 01
01
Licensed multilingual voice data
Permissioned speech datasets, structured for training and release testing — not generic audio scraping.
- ·Human voice recordings
- ·Verified transcripts
- ·Speaker metadata
- ·Language and dialect labels
- ·Accent and region coverage
- ·Emotion and tone labels
- ·Pronunciation scoring
- ·Audio quality review
- ·Consent and usage-rights documentation
- ·Model-ready metadata and delivery files
STAGE · 02
02
Human voice evaluation
Structured feedback, benchmark results, and regression data that can be used before every release.
- ·Naturalness
- ·Pronunciation
- ·Accent accuracy
- ·Speaker similarity
- ·Emotional delivery
- ·Prosody and pacing
- ·Latency perception
- ·Turn-taking
- ·Interruption handling
- ·Transcription accuracy
- ·Dubbing quality
- ·Translation fidelity
- ·Voice-agent task completion
- ·Safety and misuse risk
STAGE · 03
03
Voice safety and red-team data
Impersonation, scams, unauthorized cloning, emotional manipulation, and synthetic-speech misuse — tested before release.
- ·Impersonation red-team prompts
- ·Fraud call simulations
- ·Consent boundary testing
- ·Celebrity and public figure misuse tests
- ·Executive voice scam scenarios
- ·Family-member scam scenarios
- ·Financial, medical, and legal misuse tests
- ·Synthetic voice detection review
- ·Watermark and provenance evaluation
- ·Child and minor safety scenarios
- ·Policy compliance scoring
VOICE REGRESSION BANKS
Turn voice quality into something measurable.
Every voice model update creates risk. A model may improve in one language and regress in another. AuraOne builds reusable test sets that follow checkpoints, voices, languages, agent behavior, dubbing pipelines, and safety policies through release after release.
RELEASE REGRESSION
PASS 428 / 451
00·00 INTAKEHI-IN · ES-MX · AR-EG · EN-NGSIGN 04·18
↳ WHAT THE BANK TRACKS
- ↳New model checkpoints
- ↳New voices
- ↳New languages
- ↳New accents
- ↳New agent behaviors
- ↳New safety policies
- ↳New dubbing pipelines
- ↳New speech-to-speech releases
EXAMPLE PROGRAMS
Focused programs for the model gaps that matter.
Start with a narrow data or evaluation sprint, then expand into a continuous voice improvement loop.
TTS · PROGRAM
№ 01
Multilingual TTS expansion
For teams building synthetic voices in new markets.
↳ DELIVERABLES
- Native speaker recordings
- Regional accent coverage
- Emotion and tone samples
- Pronunciation benchmarks
- Human naturalness ratings
- Usage-rights documentation
RTA · PROGRAM
№ 02
Real-time voice agent evaluation
For teams building live conversational agents.
↳ DELIVERABLES
- Turn-taking test conversations
- Latency perception scoring
- Interruption handling review
- Noisy-environment speech
- Task-completion evaluation
- Human preference reports
ASR · PROGRAM
№ 03
Speech-to-text accuracy benchmark
For teams improving ASR across accents and noisy conditions.
↳ DELIVERABLES
- Accent-diverse audio
- Human-verified transcripts
- Word error analysis
- Domain-specific vocabulary tests
- Noise and device metadata
- Model comparison reports
DUB · PROGRAM
№ 04
Dubbing and localization QA
For teams translating voice across languages.
↳ DELIVERABLES
- Translation fidelity review
- Timing and lip-sync scoring
- Emotion preservation checks
- Cultural nuance review
- Pronunciation scoring
- Human quality ratings
RED · PROGRAM
№ 05
Voice safety red team
For teams testing abuse, cloning, and impersonation risk.
↳ DELIVERABLES
- Adversarial voice scenarios
- Consent boundary tests
- Fraud simulation datasets
- Human safety review
- Policy failure reports
- Release-readiness recommendations
ON THE RECORD · A VOICE PROGRAM
“The regression bank used to be a spreadsheet of dread. Now it’s the part of every release we look forward to running. The signed packet travels with the model.”
WHAT YOU KEEP
Your speech. Your evals. Your release record.
DATA
Licensed speech
Permissioned recordings with consent, attribution, and usage-rights documentation that travels with every file.
EVALS
Human review record
Naturalness, pronunciation, latency, turn-taking, and safety scores — with the reviewer who signed each one.
RELEASE
Regression banks you re-run
Reusable test sets that follow your voices, languages, and agents through every model checkpoint.
30-DAY PILOT
Start with a focused voice data or evaluation sprint.
Use the pilot to test a new language, evaluate a model release, validate a voice-agent experience, or benchmark your current voice quality.
PICK
- 3 target languages
- 5 accents or dialects
- 2 model use cases
- 1 evaluation goal
AURAONE DELIVERS
- Speaker recruitment
- Licensed recordings
- Verified transcripts
- Metadata and labels
- Human evaluation results
- QA report
- Model-readiness summary
RELATED LABS
Same loop. Different wavelength.
ROB · LAB
Robotics
Real-world manipulation, perception, and policy data for embodied AI teams.
OPEN LAB →SYN · LAB
Synthetic data
Coverage briefs, LLM and physics generation, privacy profiles, and governed dataset exports.
OPEN LAB →MED · LAB
Medical
Clinical workflow review for medical AI — from imaging through structured decisions.
OPEN LAB →FIN · LAB
Financial
Decisioning, compliance, and document review for regulated financial workflows.
OPEN LAB →VOICE LABS
Build voice models that work in the real world.
The next generation of AI will listen, speak, translate, interrupt, comfort, persuade, and respond in real time. We give voice teams the human data layer to build models that sound natural, understand more people, and perform reliably across the world.
↳ STARTS WITH
Licensed multilingual speech, evaluated by trained humans.
↳ LEAVES WITH
Signed datasets, regression banks, and a release record you keep.