AIF-C01 exam dumps

AIF-C01 practice question 36 of 231

AWS Certified AI Practitioner. Associate level, Amazon Web Services. Free question with the correct answer and a full explanation.

AIF-C01 Question 36

Select 3

A company needs to build a customer support chatbot capable of understanding and responding to natural language queries in both English and Spanish. The chatbot should also provide voice responses to users. Which combination of AWS managed AI/ML services can be used to implement this solution?

  1. A

    Amazon Lex for natural language understanding and dialogue management

  2. B

    Amazon Translate for translating queries between English and Spanish

  3. C

    Amazon Polly for generating voice responses

  4. D

    Amazon Comprehend for analyzing the sentiment of user queries

  5. E

    Amazon SageMaker for training a custom machine learning model for chatbot responses

Show answer and explanation

Correct answers: A, B, C

Explanation

The scenario involves building a multilingual chatbot that supports natural language understanding, translation, and voice responses. Amazon Lex provides the core conversational AI functionality, Amazon Translate enables translation between English and Spanish, and Amazon Polly generates voice responses. These managed AI services together meet all the requirements without needing custom machine learning models or sentiment analysis.

  • A. Correct.

    Amazon Lex is specifically designed for building conversational interfaces and can handle natural language understanding and dialogue management, making it a suitable choice for the chatbot's core functionality.

  • B. Correct.

    Amazon Translate allows seamless translation between English and Spanish, ensuring that the chatbot can handle queries in both languages, which is a key requirement.

  • C. Correct.

    Amazon Polly converts text to lifelike speech, enabling the chatbot to provide voice responses, as specified in the scenario.

  • D. Incorrect.

    While Amazon Comprehend can analyze sentiment and extract insights from text, it is not directly required for building the chatbot or generating voice responses in this scenario.

  • E. Incorrect.

    Amazon SageMaker is used for building, training, and deploying custom machine learning models, but the scenario can be addressed entirely through AWS's managed AI services without the need for custom model development.

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