As companies and organizations continue to expand their operations globally, the need for multi-language support in AI solutions has never been more crucial. To create a multi-language question-answering solution using Microsoft Azure AI, we will use Translator Text API for language detection and translation, and QnA Maker for setting up the question-answering part of the solution.
Creating QnA Maker Knowledge Base
The first step in creating a multi-language question and answering solution is to set up your QnA Maker knowledge base. QnA Maker is a cloud-based service from Microsoft that allows you to create a conversational question-and-answer layer over your data.
- Navigate to QnA Maker Portal and create a new knowledge base.
- Connect it to your QnA service in Azure
- Populate your knowledge base with questions and answers in the desired languages.
All the QnA Services, and the knowledge bases attached to them, are isolated by language. This requires you to have a separate knowledge base for each language you are planning to support.
Translator Text API for Language Detection and Translation
Secondly, we need a way to detect the language of the query and translate if necessary. This is where Translator Text API, a cognitive service provided by Azure, comes handy.
from azure.cognitiveservices.language.translatortext import TranslatorTextClient
from msrest.authentication import CognitiveServicesCredentials
#Create client
client = TranslatorTextClient(endpoint, CognitiveServicesCredentials(subscription_key))
#Detect Language
result = client.detect_language(["Question in unknown language"])
detected_language = result[0].language
#Translate Text
translation = client.translate(["Question in unknown language"], to='en')
translated_text = translation[0].translations[0].text
The above Python script using the Translator Text API first detects the language of the input question and then translates it to English if required. The QnA Maker can now understand and process this query in English.
Routing the Query to Correct QnA Maker
After translating the query to English, we can route this query to the related English Knowledge Base (KB). It’s as simple as making an HTTP GET or POST request to your QnA Maker knowledge base.
After receiving the response, we’ll have to translate it back to the original language before sending it to the user. Thus, ensuring that the system is user-friendly for individuals of different languages.
The Workflow
If we combine all of the above, the workflow of the multi-language question answering solution would be as following:
- User sends a query in their language.
- System detects the language of a query using Translator Text API and translates it to English.
- System then directs the query to the appropriate QnA Maker.
- QnA maker processes the request, finds the suitable answer, and send it back to the system.
- System translates the answer back to the user’s language using Translator Text API.
- Finally, the system sends the answer back to the user in their respective language.
Conclusion
To sum up, creating a multi-language question answering solution in Azure AI requires you to use multiple Azure services. Translator Text API helps to detect the language of incoming queries and translates them into English. The translated query is then processed by QnA Maker service. After receiving the answer in English, the system uses the Translator Text API once more to translate it back into the user’s language. Incorporating such a solution allows companies to break language barriers and cater to a global audience.
Practice Test
True or False: To create a multi-language question answering solution on Microsoft Azure, one can use the Text Analytics API.
- True
- False
Answer: False.
Explanation: For creating a question and answering solution, the QnA Maker service would be more appropriate, not the Text Analytics API.
Which Microsoft Azure service can be used to create a multi-language question answering solution?
- a) Text Analytics API
- b) QnA Maker
- c) Bot Composer
- d) LUIS
Answer: b) QnA Maker.
Explanation: QnA Maker is a cloud-based service from Microsoft Azure that creates a question and answer layer over your data. It can be leveraged to build a multi-language Q&A solution.
True or False: Microsoft’s QnA Maker API has a language limitation and can only handle queries in English.
- True
- False
Answer: False.
Explanation: QnA Maker API supports multiple languages for creating a question and answer solution.
Which of the following is not supported by a multi-language question-answering solution on Azure?
- a) Arabic
- b) French
- c) Swahili
- d) Japanese
Answer: c) Swahili.
Explanation: Currently, Swahili is not supported in the language understanding service.
True or False: Microsoft’s Azure provides only some pre-selected languages for creating a multi-language question and answering solution.
- True
- False
Answer: True.
Explanation: While Azure has support for multiple languages, the list is pre-selected and not all languages are available for question-answer solutions.
Could Azure Bot service be integrated with QnA Maker for a multi-language Q&A solution?
- a) Yes
- b) No
Answer: a) Yes.
Explanation: Azure Bot Service can integrate with a QnA knowledge base to create conversationally rich bots that are capable of answering questions in multiple languages.
True or False: Azure Bot Service and QnA Maker integration supports real-time language translation.
- True
- False
Answer: True.
Explanation: Azure Bot Service integrated with QnA Maker does support real-time translation, enabling multi-language conversation capabilities.
Which tool can be used to train the multi-language model in Microsoft Azure?
- a) Form Recognizer
- b) LUIS
- c) Translator Text
- d) Computer Vision
Answer: b) LUIS
Explanation: Language Understanding Intelligent Service (LUIS) helps in building custom machine learning models to predict responses and train the model in multiple languages.
True or False: Azure QnA Maker supports collaborative editing of the knowledge base.
- True
- False
Answer: True.
Explanation: Azure QnA Maker provides the feature to collaborate with your team in real time.
Which Microsoft Azure service allows real-time conversation translation to multiple languages?
- a) Translator Text
- b) Speech Service
- c) LUIS
- d) Azure Bot Service
Answer: d) Azure Bot Service.
Explanation: The Azure Bot Service, when integrated with Translator Text, can support real-time conversation translation in multiple languages.
Interview Questions
What is the first step to consider when designing a multi-language question answering solution on Microsoft Azure?
The first step to consider when designing a multi-language question answering solution is defining the languages you want your solution to support and subsequently understanding the language capabilities that Azure AI provides.
What Azure AI service can be used to translate text from one language to another?
Azure Cognitive Services “Translator text API” can be used to translate text from one language to another.
Which tool can be used for implementing a multi-language question answering solution that involves understanding user queries?
Azure’s Language Understanding (LUIS) can be used to understand user queries in a multi-language question answering solution.
How can Azure’s QnA Maker be utilized in a multi-language question-answering solution?
Azure’s QnA Maker can be used to create a knowledge base in multiple languages that supports your solution. This knowledge base can then be queried by the bot to provide answers in the user’s language.
What role does the Bing Spell Check API play in a multi-language question answering solution?
The Bing Spell Check API is used to correct user spelling errors in queries, providing more accurate translation and understanding of the user’s intents.
How does multi-language processing improve the user experience in AI solutions?
It increases user engagement and satisfaction by providing localized responses, making AI solutions more accessible to non-English speaking users.
How can you test your multi-language question answering solution in Microsoft Azure?
You can test your solution using Azure Bot Service’s testing in Web Chat feature. It allows you to interact with your bot directly within the Azure portal.
Can Azure AI handle real-time language processing?
Yes, Azure Cognitive Services support real-time language processing.
What is one challenge in creating multi-language question answering solutions?
One challenge is understanding the nuances and complexities of various languages to correctly interpret the intent of the question in different languages.
In what format does the Translator Text API accept text for translation?
The Translator Text API accepts text as plaintext strings, not in any special format.
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