Question

A medical transcription team uses Azure Speech in Foundry Tools to convert dictated notes into text. The default speech-to-text model frequently misrecognizes specialized drug names and clinical terminology, producing inaccurate transcripts. The team wants to improve recognition accuracy for this vocabulary without abandoning Azure Speech. What should they do?

Accepted Answer

Create a Custom Speech model trained with domain-specific vocabulary and sample audio, then deploy it as the recognition endpoint

Answer

Increase the audio sample rate of the recordings so the default model captures more detail

Answer

Switch from speech-to-text to text-to-speech synthesis for the dictated notes

Answer

Enable profanity filtering so unrecognized clinical terms are removed from the transcript