AI-102 exam dumps

AI-102 practice question 240 of 493

Designing and Implementing a Microsoft Azure AI Solution. Professional level, Microsoft. Free question with the correct answer and a full explanation.

AI-102 Question 240

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You are creating a speech-to-speech translation solution using the Azure AI Speech service. Your solution must: 1) Translate spoken English into spoken French in real-time, 2) Ensure that the solution can handle different accents in the input speech, and 3) Provide an audible French output with natural intonation. Which combination of Azure AI Speech service features should you use?

  1. A

    Speech-to-Text for recognizing English speech

  2. B

    Text Translation for translating text from English to French

  3. C

    Custom Neural Voice for generating French audio output

  4. D

    Speech Translation for direct speech-to-speech translation

  5. E

    Speaker Recognition for identifying the user’s voice

Show answer and explanation

Correct answers: A, B, C

Explanation

To achieve real-time speech-to-speech translation with natural intonation, you must first use Speech-to-Text to transcribe the spoken English input. The text is then translated into French using Text Translation. Finally, Custom Neural Voice generates high-quality, natural French speech output. This modular approach ensures flexibility and high-quality results compared to using Speech Translation directly.

  • A. Correct.

    Speech-to-Text is required to accurately transcribe the spoken English input into text, considering diverse accents.

  • B. Correct.

    Text Translation is needed to translate the transcribed English text into French text.

  • C. Correct.

    Custom Neural Voice is used to generate natural, human-like French audio output, meeting the requirement for natural intonation.

  • D. Incorrect.

    Speech Translation could simplify the pipeline but does not allow the flexibility of customizing the voice output or ensuring high-quality translation with separate components.

  • E. Incorrect.

    Speaker Recognition is not relevant for this scenario as identifying who is speaking is not a requirement.

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