Microsoft Azure AI Engineer Associate AI-102 Practice Question
You are building a .NET desktop application with the Azure AI Speech SDK. The application must run on laptops that can lose Internet connectivity. It must:
Detect the wake phrase "Contoso start" locally so that no network call is required.
After the wake phrase is detected, capture the subsequent audio and classify the spoken command against intents trained in a Conversational Language Understanding (CLU) project deployed in Azure. Which pair of Speech SDK objects should you create to satisfy both requirements?
Instantiate a KeywordRecognizer for the wake phrase and an IntentRecognizer for the command utterance.
Start with a TranslationRecognizer for the wake phrase and then pass audio to an IntentDataSource object.
Create a PushAudioInputStream for the wake phrase and a SpeechSynthesizer for the command utterance.
Use a SpeechRecognizer with a PhraseListGrammar for the wake phrase and intents.
A KeywordRecognizer can perform on-device keyword spotting by loading a compiled KeywordRecognitionModel, so the wake phrase is detected without contacting Azure. Once the wake word is detected you can hand over the same microphone stream to an IntentRecognizer, which streams audio to the cloud and returns the top intent from your CLU project. A SpeechRecognizer or TranslationRecognizer cannot directly invoke a CLU intent model, PhraseListGrammar does not do intent classification, and PushAudioInputStream or SpeechSynthesizer cannot perform recognition by themselves.
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Microsoft Azure AI Engineer Associate AI-102
Implement natural language processing solutions
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