Understanding Every Child

Speech recognition trained
specifically on children ages 3-16.
Built for developmental speech patterns, high-noise environments, and real-world child interactions.

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Easy integration
<400ms latency
High concurrency
Compliant
Private

Built for How Children Speak

The goal is not to normalize or correct children's speech, but to understand it, reliably, respectfully, and over time.

Child-Specific Phonetics

Recognition built around how children form sounds and words at each developmental stage. Young children substitute sounds, simplify consonant clusters, and articulate differently than adults. Our models expect this rather than penalizing it.

Developmental Awareness

Models that adapt to age-dependent articulation and pacing. A 4-year-old speaks differently than a 7-year-old. The system adjusts expectations based on the child's developmental stage, improving accuracy across the full range of childhood.

Natural Repair Behaviors

Understanding persistence and self-correction in real conversations. Kids restart sentences. They change their minds mid-word. They correct themselves. The system recognizes these patterns as normal rather than errors.

Intent Understanding

Goes beyond transcription. Understands what children mean, accounting for creative word usage, made-up words, and context-dependent meaning.

Noise-Robust

Optimized for real-world environments where children use devices. Background noise, echo, and variable microphone quality handled gracefully.

Why Generic ASR Fails Children

General-purpose speech recognition is trained on adult speech. But children speak differently: developmental articulation, incomplete sentences, creative vocabulary, and unpredictable patterns. When recognition fails, the experience fails.

Challenge	Generic ASR	UG Labs ASR
"I wanna go to da park"	"I want to go to the pork"	"I wanna go to da park" (intent: go to park)
Hesitations and fillers	Transcribed literally, confusing context	Filtered intelligently, preserving meaning
Made-up words in play	Error or closest adult word	Recognized as creative language, context preserved
Quiet or mumbled speech	Low confidence or failure	Robust recognition with confidence scoring

Voice Handled End-to-End

UG's SDK handles voice capture, processing, and transcription as part of a compliant, production-grade runtime. Add voice to your product without the infrastructure burden.

You Don't Need To

Handle or store raw child audio
Build voice processing pipelines
Manage COPPA/GDPR-K obligations for voice data
Maintain and tune speech models
Implement PII detection in audio
Build consent management for voice

UG Manages

Secure voice ingestion from device to cloud
Child-specific speech recognition
Real-time safety and PII reduction
Consent-aware data handling
Compliance with child data regulations
Continuous model improvement

Built on Consent and Real Use

Our speech models are built on consent, transparency, and privacy by design.

Explicit Parental Consent

Clear disclosure of purpose and usage with every data collection. Parents know what's being collected, why, and how it's used. Consent is revocable, and deletion requests are honored.

Data Minimization by Default

Anonymization, aggregation, and revocable consent built into governance. We collect only what's needed to provide the service. Data is processed to remove identifying information.

No Scraping, No Profiles

No data collected without permission. No identity-level profiles created from children's voice data. Data is used only to improve the service.

Read About Data Collection

Built for Production

Streaming & Batch

Real-time streaming for conversational experiences, or batch processing for recorded audio. Same accuracy, flexible deployment options for any use case.

Platform Support

SDKs for major platforms and frameworks. Integration documentation and sample implementations. Support for mobile, web, smart devices, and games.

Test Child Speech Recognition

Record your voice or a child's voice and see the transcription in real-time. Compare the accuracy yourself.