A large company has developed a BI application that generates reports and dashboards using data collected from various operational metrics. The company wants to provide executives with an enhanced experience so they can use natural language to get data from the reports. The company wants the executives to be able ask questions using written and spoken interfaces.
Which combination of services can be used to build this conversational interface? (Choose three.)
To create a conversational interface that allows executives to ask questions using both written and spoken interfaces, three services are essential. Amazon Lex can be used to build the conversational interface, interpreting both text and voice inputs using natural language understanding (NLU) capabilities. Amazon Polly converts text responses into spoken language, enhancing the interaction by providing voice output. Finally, Amazon Transcribe converts spoken language into text, allowing voice inputs to be processed by Amazon Lex. This combination enables a seamless question-and-answer experience for the executives using both written and spoken interfaces.
C - voice and text interface E - understanding F - Speech to text
Why would I need to transcribe while I have Lex that do the NLU part? It would be more reasonable to select Either Connect (B) or Polly (D) if the specs to generate output speech.
E - is more to express the "feeling" or "mood". We would rather need something, that can speak to the customer. So my suggestion is c,d,f
The question states that the company wants to "provide executives with an enhanced experience so they can use natural language to get data from the reports." The key phrase here is "use natural language," which implies that the executives will be interacting with the system using human-like language, either written or spoken. To understand and interpret natural language inputs from users, whether written or spoken, the system needs to have natural language understanding (NLU) or natural language processing (NLP) capabilities. Without NLU/NLP capabilities, the system would not be able to make sense of the executives' natural language queries and extract the relevant information to retrieve data from the reports and dashboards. Services like Amazon Lex and Amazon Comprehend are specifically designed to provide NLU and NLP functionalities, respectively. Amazon Lex uses NLU models to understand the intent and extract relevant information from user inputs, while Amazon Comprehend provides NLP capabilities to analyze and extract insights from text data.
If we need to build written and spoken interfaces we need : F - Transcribe (speech to text) D- Polly (text ot speech) And for chatbot: E - Lex
*C - Lex So C,D,F
I second that, the keyword here is "conversational interface". so, no conversation without Amazon Lex
A. NO - Alexa for Business B. NO - Amazon Connect for call centers C. YES - Amazon Lex for chatbots D. YES - Lex Text-to-Speech E. NO - Amazon Comprehend is for topic extraction and sentiment analysis, Transcribe already does it F. YES - Transcribe Speech-to-Text
Transcribe does not do sentiment analysis and topic extraction it just generates transcript from speech so we need Amazon Comprehend
why does aws use muliplt service for tts and stt?
Agree with CDF
Amazon Polly is essential for providing spoken responses in a conversational interface, it doesn't directly handle the natural language understanding and processing aspect, which is why it wasn't included as one of the top three services for building the conversational interface in this scenario. Correct is C, E, F
I will go with: lex for the chat interface comprehend for getting insights from reports Polly for text-to-speech transformation https://aws.amazon.com/blogs/machine-learning/deriving-conversational-insights-from-invoices-with-amazon-textract-amazon-comprehend-and-amazon-lex/
CEF is correct
Answer is CEF --> Input can be speech but the output to the user will be text (as nothing specific is mentioned) using Lex for conversational interface, Transcribe to convert speech to text (if input is speech) and Comprehend for insights from text
No, don't need E Comprehend because the report has already been generated.
Amazon Lex (C): This service is crucial for building conversational interfaces. It provides the capabilities to understand and interpret user input in natural language, which is essential for understanding the questions asked by executives. Amazon Transcribe (F): For a spoken interface, you need a service that can convert speech into text. Amazon Transcribe does exactly this, allowing the system to process spoken questions by converting them into text that can then be interpreted by Amazon Lex. Amazon Polly (D): To enhance the user experience by responding to inquiries not only in text but also in spoken form, Amazon Polly is ideal. It converts text responses into lifelike speech, allowing the system to verbally communicate with the executives. Together, these three services (Amazon Lex, Amazon Transcribe, and Amazon Polly) will enable a comprehensive conversational interface for the BI application, catering to both written and spoken queries and responses
CDF -> CEF. you dont need comprehend in this scenario.
C. Amazon Lex: It provides advanced deep learning functionalities of automatic speech recognition (ASR) for converting speech to text, and natural language understanding (NLU) to recognize the intent of the text, enabling you to build applications with highly engaging user experiences and lifelike conversational interactions. D. Amazon Polly: This service turns text into lifelike speech using deep learning. It would enable the BI application to deliver the answers to the executives' questions in a spoken format. F. Amazon Transcribe: This is an automatic speech recognition (ASR) service that makes it easy for developers to add speech-to-text capability to their applications. This would be necessary for the BI application to interpret spoken questions from the executives.
For a BI application where executives can ask questions using written and spoken interfaces, the following combination of services would be suitable: Amazon Lex (Option C): To build the core conversational interface that understands and processes natural language queries. Amazon Polly (Option D): To provide spoken responses to written queries, giving a more interactive experience for users who are not using the voice interface. Amazon Transcribe (Option F): To convert spoken queries into text that can be understood by Amazon Lex. These three services would work together to provide a comprehensive conversational interface that allows for both text and voice interactions, meeting the requirements of the scenario provided.
I believe Answer should be CDF C: Lex D: Polly F: Transcribe
Lex for bot service, Polly for text-to-speech (answer) and Transcribe for speech-to-text (question).
Alexa for Business: Handles the voice interaction, converting spoken queries into text and providing the voice interface that executives use to interact with the BI application. Amazon Lex: Processes the text input (converted by Alexa) and understands the intent behind the queries, enabling the conversational interface. Amazon Polly: Optional but useful if you want to convert the textual responses from the BI application back into spoken responses, providing a complete voice-based interaction.