voice-to-sign-services

Purpose

This research explores services that translate voice/audio/text into sign language—essentially the inverse of Whisper (which does speech-to-text). These tools convert spoken language into visual sign language representations, typically using AI-powered avatars.

Key Findings

Yes, these services exist - Multiple commercial and open-source options available
Avatar-based approach dominates - Most solutions use 3D/2D animated signers
Real-time translation achievable - Sub-second latency on modern systems
ASL/BSL most supported - Other sign languages have limited coverage
Google SignGemma - Major upcoming open model (Q4 2025)

Commercial Services

Enterprise/Production-Ready

Signapse AI

Website: signapse.ai
Languages: ASL, BSL
Features:
- Photo-realistic AI-generated signing avatars
- Real-time generative AI translation
- Video, events, signage, and announcement translation
- Deaf translators involved in development
Use Case: UK train stations (5,000+ BSL announcements daily)
Status: Production, 2025 Slator Language AI 50 Under 50 winner

Hand Talk

Website: handtalk.me
Languages: ASL, Libras (Brazilian)
Features:
- Pocket translator app (iOS/Android)
- Text and audio to sign language
- Named “World’s Best Social App” by United Nations
Users: 3+ million
Status: Production

SignForDeaf

Website: signfordeaf.com
Features:
- Bidirectional: Voice/text ↔ Sign language
- Website integration (clickable sentences)
- Video subtitle translation
- PDF document translation
Status: Production

Signtel Interpreter

Website: signtelinc.com
Features:
- 30,000 word vocabulary
- Voice recognition to sign language video
- Seamless word-to-sign connections
Status: Production

Emerging/Specialized

Sign-Speak / CaptionASL

Website: sign-speak.com
Features:
- ASL-to-voice AND voice-to-ASL
- Real-time captioning
- API & SDK available
- Zoom/Google Meet/Teams integration
Status: Pioneers Program (early access)

Slait AI

Website: slait.ai
Languages: ASL
Features:
- Real-time video communication SaaS
- B2B focus (customer service applications)
Limitation: Experimental, not human-level interpretation
Status: Production (limited)

CODA (Israeli Startup)

Features:
- AI-generated avatars
- Real-time spoken-to-sign translation
- Video content accessibility focus
Status: Development

Terp 360

Languages: English/Swahili → Kenyan Sign Language
Roadmap: ASL by mid-2027
Features: Web-based, real-time, 3D avatars
Status: Production (regional)

SignAvatar

Website: signavatar.org
Use Case: Airport PA system integration
Features:
- Works as software layer on existing PA systems
- 3-4 second translation latency
- Multi-language visual announcements
Deployment: Belgrade Nikola Tesla Airport (trial)
Status: Pilot

Developer APIs & SDKs

Production APIs

VSL Labs API

Website: vsllabs.com
Output: English text → 3D ASL
Features: Patented translation API
Integration: Apps, websites, meetings
Status: Production

Sign-Speak API & SDK

Website: sign-speak.com/solution
Features:
- Few lines of code integration
- Bidirectional translation
- Video platform integration
Status: Available

SignAll SDK

Announcement: Google Developers Blog
Built On: MediaPipe hand tracking
Platforms: Windows, iOS, Android, Web
Use Cases:
- Video calls by signing contact names
- Navigation address input
- Fast-food kiosk ordering
Status: Production

Coming Soon

Google SignGemma

Announcement: Google I/O 2025
Architecture: Gemini Nano + Vision Transformer
Training: 10,000+ hours annotated ASL video
Features:
- On-device processing (low latency)
- ASL → English text (initial focus)
- Open model
Access:
- Preview available at goo.gle/SignGemma
- TensorFlow Lite package
- GitHub sample code
- Hosted API
Full Release: Q4 2025
Note: Currently ASL→text; text/voice→sign direction unclear

Open Source

sign-language-translator (Python)

PyPI: sign-language-translator
GitHub: sign-language-translator/sign-language-translator
Features:
- Full sentence translation (not just alphabet)
- Framework for custom regional sign languages
- CLI included
- Text ↔ sign language translation
Documentation: Read the Docs

AudioToSignLanguageConverter

GitHub: sahilkhoslaa/AudioToSignLanguageConverter
Type: Web application
Features: Audio/voice input → Sign language output

Cloud Platform Solutions

AWS GenASL

Documentation: AWS Blog
Input: Audio, video, or text
Output: ASL avatar video
AWS Services Used:
- Amazon Transcribe (speech-to-text)
- Amazon SageMaker (ML)
- Amazon Bedrock (generative AI)
Status: Available

Hardware Solutions

BrightSign Glove

Website: brightsignglove.com
Type: Wearable glove + app
Direction: Sign language → voice/text (inverse of query focus)
Languages: 30+ spoken languages
Features:
- Real-time translation
- 450+ voice choices
- Cloud sync
- iOS/Android app
Note: Primarily sign-to-voice, but bidirectional features in development

Comparison: Voice-to-Sign vs Whisper (Speech-to-Text)

Aspect	Whisper (STT)	Voice-to-Sign Services
Input	Audio/speech	Audio/speech/text
Output	Text	Animated avatar video
Latency	<1 second	1-4 seconds typically
Open Source	Yes (OpenAI)	Limited (Python lib, SignGemma coming)
Languages	100+	ASL/BSL primarily
Self-hosted	Yes	Mostly cloud-dependent
Maturity	Very mature	Emerging

Technical Approaches

How Voice-to-Sign Works

Speech Recognition: Audio → text (using Whisper, Google STT, etc.)
Text Processing: NLP to understand meaning and context
Gloss Conversion: Text → sign language notation (gloss)
Sign Selection: AI selects appropriate signs based on:
- Context and meaning
- Grammar rules (sign language has different grammar)
- Non-manual markers (facial expressions)
Avatar Animation: Generate realistic signing animation

Key Technical Challenges

Grammar differences: Sign languages have their own syntax
Non-manual markers: Facial expressions carry meaning
Regional variations: ASL differs from BSL, LSF, etc.
Real-time performance: Low latency required for conversation
Avatar realism: Uncanny valley concerns

Accessibility Statistics

70 million people use sign language as primary communication globally
300+ different sign languages worldwide
711 million projected deaf population by 2050
23% of deaf community had interpreter at live events

Why Sign Language, Not Just Captions?

A common question: “If we have speech-to-text (captions), why do we need speech-to-sign?”

Sign Language is a Native Language

For many deaf individuals (especially those deaf from birth), sign language is their first and native language. Written English/text is effectively a second language with completely different:

Grammar: ASL uses topic-comment structure, not subject-verb-object
Syntax: Time markers come first; spatial relationships are simultaneous
Expression: Facial expressions and body movement carry grammatical meaning

The Literacy Challenge

Statistic	Implication
Average deaf HS graduate reads at 4th-6th grade level	Complex captions may be inaccessible
Reading requires phonological awareness	Harder to develop without hearing
Sign language = visual-spatial	Text = linear sequential processing

This isn’t about intelligence—it’s about language acquisition. Deaf children who learn sign language early develop normal language abilities; the challenge is that written language maps to a spoken language they may never have heard.

Cognitive Load Comparison

Captions: Read text + watch video = divided attention, second-language processing
Sign language avatar: Receive in native language = natural comprehension

Analogy

Asking “why not just use captions?” is like asking “why do Spanish speakers need Spanish audio if we can add English subtitles?”

Subtitles in a second language work, but native-language content is fundamentally more accessible.

Who Benefits Most from Sign Language Translation

Deaf from birth with sign language as L1
Deaf children still developing literacy
Anyone with low text literacy (cognitive disabilities, learning differences)
Elderly deaf who may have declining reading vision
Complex content where reading speed can’t keep up