platform · Microsoft
Speech Recognition & Transcription with Azure OpenAI
Speech Recognition & Transcription built on Azure OpenAI, chosen where it genuinely fits, and swapped where it does not.
- Category
- platform
- Vendor
- Microsoft
- Alternatives we also use
- 6
Why Azure OpenAI for this
Word error rate on clean American English tells you nothing about your call centre in Coimbatore. We measure on your actual recordings.
Azure OpenAI is strongest at enterprise compliance posture and integration with existing Microsoft estates. For speech recognition & transcription that matters because the failure modes of this kind of system tend to cluster exactly there.
The honest trade-off: quota management and regional capacity can constrain scaling at short notice. We say that up front because a stack chosen for fashion rather than fit becomes someone's migration project two years later. Integration comes before intelligence. A model that cannot reach your systems of record is a demo with good manners.
You own the code, the models where they are open-weight, and the documentation to run it without us.
The honest assessment
- What it is
- OpenAI models under Azure's compliance envelope and enterprise agreements.
- Strongest at
- enterprise compliance posture and integration with existing Microsoft estates
- Trade-off
- quota management and regional capacity can constrain scaling at short notice
- Category
- platform
We are not a reseller for Microsoft and hold no commission on this choice. Where a different option fits your workload better, the recommendation will say so. That is the entire value of asking us.
What is included
- Domain vocabulary tuning for your terminology
- Speaker diarisation, who said what
- Indian language and accent handling, including code-mixing
- Timestamped output linked to the audio
- Word error rate measured on your own recordings
- Integration with your EMR, CRM or case system
Questions
How accurate is it for Indian accents?
Good and improving, but the honest answer depends on audio quality, accent and domain. We benchmark word error rate on your own recordings before you commit.
Can it separate speakers?
Yes, speaker diarisation labels who said what, which is essential for clinical, legal and contact-centre records.
Does the audio leave our environment?
Only if you allow it. We can deploy fully on-premise where confidentiality or regulation requires it.
Building with Azure OpenAI?
Bring us the workload and we will tell you whether this is the right stack for it.
Or email bd@dtrasglobal.com · call +91 74118 77878