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Implement natural language processing solutionshardMultiple SelectObjective-mapped

AI-102 Practice Question: Implement natural language processing solutions

A company uses Azure AI Speech to provide real-time transcription for customer support calls. The solution must handle multiple languages and filter out profanity. Which THREE configurations are needed?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Set the SpeechConfig.SpeechRecognitionLanguage property

To achieve real-time transcription with multi-language support and profanity filtering using Azure AI Speech, three configurations are required. First, set the `SpeechConfig.SpeechRecognitionLanguage` property (Option C) to specify the source language for accurate transcription. Second, use the Speech SDK with intermediate results (Option D) to provide real-time feedback during the call. Third, enable the ProfanityFilter option in the Speech SDK (Option E) to filter out profanity. Option A (Batch Transcription) is incorrect because it is not real-time. Option B (custom speech model per language) is unnecessary because the standard prebuilt models support multiple languages and profanity filtering without customization.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Use the Batch Transcription REST API

    Why it's wrong here

    Batch API is not for real-time transcription.

  • Deploy a custom speech model for each language

    Why it's wrong here

    Custom models are not required for profanity filtering.

  • Set the SpeechConfig.SpeechRecognitionLanguage property

    Why this is correct

    Sets the source language for recognition.

  • Use the Speech SDK with intermediate results

    Why this is correct

    Intermediate results enable real-time display.

  • Enable the ProfanityFilter option in the Speech SDK

    Why this is correct

    Filters profanity in transcription.

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