Turn audio archives into usable data
Audio files should not stay buried in storage. Transcription turns them into text that can be searched and analyzed.
For calls and meetings
Customer conversations, meeting recordings and operator dialogues can share the same STT workflow.
Scale through the API
If you have many audio files, an API-based transcription pipeline is more reliable than manual uploads.
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
Upload an audio file.
2
Wait for transcription to complete.
3
Export or integrate the finished text.
Which workflow fits your use case?
STT language pages
API and developer paths
Use case pages
Related pages
Frequently asked questions
Which languages can Aisha transcribe?
Aisha STT is used for Uzbek, Russian and English transcription workflows.
Can MP3 files be transcribed?
Supported formats and limits are listed in the STT API documentation.
Is speaker diarization available?
Yes. Diarization is available for supported workflows.