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.
AI voice workflow
Multilingual speech to text
Multilingual speech to text: turn recordings into text you can review, search and use in your product. Start with a representative sample in your target language.
Aisha AI · Updated
Use case
Multilingual recordings
Transcript review
Language switches
International support
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.
Define a useful result
Decide whether you need a verbatim transcript, a translation or a summary. These are different outputs; confirm what your selected model returns before processing a full recording.
STT and transcription workflow
Once audio becomes text, the transcript can feed CRM, search, QA review, summaries or Call Metrics workflows.
App first, API when needed
Teams can validate the workflow in the Space app, then automate it through the API. Format, limits and endpoint details should stay governed by the official documentation.
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
Prepare the audio source.
2
Transcribe it through the STT API or Space app.
3
Connect the transcript to CRM, search or analytics.
Which workflow fits your use case?
STT language pages
API and developer paths
Use case pages
Related pages
Frequently asked questions
Is Aisha suitable for Multilingual speech to text?
Start by testing preparing and reviewing transcripts for recordings in different languages with representative material. Confirm the target language and required features in Space or the API documentation before planning a full integration.
Can this work through an API?
Yes. The speech-to-text API supports audio submission, status checks and transcript retrieval.
Where are exact formats and limits documented?
Supported formats, limits and endpoint details are handled in the official Aisha API documentation.