Putting sign language AI into users’ hands
Yet this technological revolution has not reached the world’s more than 200 sign languages — and the estimated 70 million Deaf and hard of hearing people who use them.Today, we’re introducing a massively multilingual sign-language-to-text (SL2T) translation model that marks a breakthrough in quality and generality. With it, we are bringing sign language AI out of the lab and into consumer products for the first time: SL2T powers sign-to-text dictation in Gboard and Live Transcribe on Pixel 11, starting with American Sign Language (ASL) to English. More devices are coming soon, and additional languages will follow.Similarly to how hearing users can use dictation to speak instead of typing, this feature enables Deaf users to sign to their phone anywhere they’d normally type.
- ▪Yet this technological revolution has not reached the world’s more than 200 sign languages — and the estimated 70 million Deaf and hard of hearing people who use them.Today, we’re introducing a massively multilingual sign-language-to-text (
- ▪With it, we are bringing sign language AI out of the lab and into consumer products for the first time: SL2T powers sign-to-text dictation in Gboard and Live Transcribe on Pixel 11, starting with American Sign Language (ASL) to English.
- ▪More devices are coming soon, and additional languages will follow.Similarly to how hearing users can use dictation to speak instead of typing, this feature enables Deaf users to sign to their phone anywhere they’d normally type.
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| Original publisher | DeepMind |
| Canonical URL | https://deepmind.google/blog/putting-sign-language-ai-into-users-hands/ |
| Publication time | Wed, 12 Aug 2026 14:01:59 +0000 |
| Retrieval time | 2026-08-12T14:06:31.548Z |
| Last seen | 2026-08-12T14:06:31.548Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | WkOXwSX3Yrs_ · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
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| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
August 12, 2026 ModelsPutting sign language AI into users’ handsGoogle DeepMind Sign Language Team Share CopiedIntroducing sign-language-to-text (SL2T), our breakthrough model powering new sign language features for Deaf and hard of hearing users.AI's ability to process spoken languages has advanced rapidly over recent decades, enabling automatic translation, dictation, and conversational interfaces that feel effortless to hearing users. Yet this technological revolution has not reached the world’s more than 200 sign languages — and the estimated 70 million Deaf and hard of hearing people who use them.Today, we’re introducing a massively multilingual sign-language-to-text (SL2T) translation model that marks a breakthrough in quality and generality.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at DeepMind.
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