Speech Recognition
ASRSpeech Recognition
Providers using this tag (51)
Ranked by API Evangelist rating — Exemplar and Strong are expanded by default.
Strong 6 Solid coverage with minor gaps
Developing 10 Usable, with meaningful gaps to close
Thin 10 Limited public surface area
Emerging 12 Early or largely undocumented
Minimal 12 Almost no public developer surface
Unrated 1 Not yet scored
APIs with this tag (17)
Ranked by the provider's API Evangelist rating — the Kin Score is scored per provider, not per API, so every API of a provider shares its band. How the rating works →
Strong 4 Solid coverage with minor gaps
Developing 6 Usable, with meaningful gaps to close
Thin 2 Limited public surface area
Emerging 5 Early or largely undocumented
Companies reaching this through an API (4)
These companies publish an API, specification or operation carrying “Speech Recognition” but do not classify their business under it. Listed unranked and kept out of the count above, because one tagged operation is not a statement about what a company does.
Score breakdown
Where this tag sits
Related tags
Where this tag comes from
Cohort brief
Auto-generatedThe 47 providers in the APIs.io catalog tagged Speech Recognition, scored on the Kin Score. Every figure below is computed from the catalog — nothing here is written.
| Facet | This cohort | Catalog | Difference | Scored |
|---|---|---|---|---|
| Developer Ergonomics | 37 | 23.2 | +13.8 | 47 |
| Access Clarity | 37.7 | 23.9 | +13.8 | 47 |
| Operational Transparency | 21.5 | 13 | +8.5 | 47 |
| Discoverability | 63.2 | 57.9 | +5.3 | 47 |
| Contract Quality | 20.5 | 17.2 | +3.3 | 47 |
| Contract Governance | 7.1 | 6.5 | +0.6 | 47 |
A facet is averaged over the members that carry it, not over the whole cohort — the “Scored” column is that count. Averaging an absent facet as zero would score our own coverage gaps as the providers’ posture.
| Artifact | This cohort | Catalog | Difference |
|---|---|---|---|
| MCP server (any) | 13% | 13% | 0 |
| MCP server (first-party) | 15% | 12% | +3 |
| Agent Skills | 0% | 0% | 0 |
| OAuth scopes | 8% | 11% | -3 |
| Security | 98% | 98% | 0 |
| Arazzo workflows | 0% | 2% | -2 |
| Governance rules | 10% | 16% | -6 |
mcp_pct counts any mcp/ artifact including ones API Evangelist derived from the provider OpenAPI; mcp_first_party_pct counts only servers the provider publishes. Prefer the latter.
- 1 Google Dialogflow 66.1
- 2 PyannoteAI 61.2
- 3 SLNG 59.6
- 4 ASAPP 57.5
- 5 Amazon Transcribe 57.1
- 6 StepFun 54.4
- 7 VerbIT 53.8
- 8 Allo-Media 50.6
- 9 Suki AI 48.3
- 10 Moore Threads 48.1
- 1 Google Dialogflow 38.2
- 2 Allo-Media 37.8
- 3 PyannoteAI 37.4
- 4 SLNG 32.1
- 5 Polyai 31.3
- 6 ASAPP 30.8
- 7 StepFun 30.6
- 8 Kotoba 30
- 9 Moore Threads 28.1
- 10 Reson8 28.1
Coverage caveat. 39 of 47 scored members had under half their catalog-attributable points satisfied at all (catalog_earned / catalog_max < 0.5). They are INCLUDED in the mean above. A large share here means the cohort mean is partly a measurement of how far our enrichment reached, not only of how these providers publish.Generated from the catalog build of 24 October 2026, across 31984 providers, using the same computation served by the APIs.io cohort API. Briefs are published for rosters of 5 or more scored providers; below that a distribution is not meaningful.
Work with this as data
Every tag here is available over the APIs.io API and to AI agents over MCP.