QuestionQ104

VerifiedImplement text analysis solutions

You are creating a text-to-speech solution using Azure Speech in Foundry Tools that reads instructions aloud from a script contained in a text file.

You notice that the solution frequently mispronounces technical terms.

You need to stop these incorrect pronunciations from occurring. The solution must minimize development effort.

What should you do?

Explanation

The SSML phoneme element allows you to specify the exact pronunciation of a word using a phonetic alphabet such as IPA or SAPI. This directly addresses mispronunciation of specific technical terms with minimal effort, since you only need to annotate the problematic words in the SSML markup rather than retrain a model. In contrast, say-as is meant for interpreting content types (like dates or numbers) rather than correcting phonetic pronunciation, prosody adjusts pitch/rate/volume rather than pronunciation, custom neural voice training requires substantial data collection and model training effort, and Whisper is a speech-to-text model, not applicable to a text-to-speech pronunciation issue.

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