What does it solve?
Use transcripts to find information in calls, meetings and voice messages. Keep the source recording so reviewers can check uncertain passages.
Quick answer
Speech to text converts recorded speech into a transcript. Review it against the audio before using it for search, summaries or customer records.
How does it connect?
Try a short sample in Space. For repeated work, check the API reference for supported languages, request formats, limits and result retrieval.
Which languages should I test?
Test every language and regional accent your audience uses. Evaluate language switches separately, and confirm support for your chosen service rather than assuming TTS and STT have identical catalogs.
Return audio data to your product
The STT API helps teams extract text from recordings without manual transcription. This matters for call-center, CRM and compliance workflows.
Diarization and status checks
Multi-speaker recordings may need speaker segments, and longer files need task status tracking.
Foundation for call analytics
Transcripts can feed intent detection, sentiment review, quality checks and operator workload analysis.
What to check before launch
Evaluate results with your own material. Keep separate results for each language and recording or playback condition.
Try a representative sample
Transcribe a short recording. Compare names, numbers, negations and language switches against the audio.
Connect it to the product
Keep API credentials on your server. Check documented formats, limits and response states, and test a failed request before automating the process.
Review each language
Do not generalize one language result to the entire catalog. Ask someone familiar with the target accent and terminology to review the output.
How it works
1
Send the audio file through the API.
2
Check task status or wait for a webhook.
3
Push the transcript to CRM or analytics.
Which workflow fits your use case?
STT language pages
API and developer paths
Use case pages
Related pages
Frequently asked questions
Can the speech-to-text API process Uzbek audio?
Yes. Aisha STT is used for Uzbek, Russian and English transcription workflows.
Can it process larger files?
Larger audio can be handled through the asynchronous task flow.
Where are the endpoints documented?
The speech-to-text API documentation explains upload, status and transcript retrieval.