This is a follow-up blog to
Which AI am I ? [Azure AI Applied Services : Part 1]
Azure Cognitive Services: Vision API's [Azure AI Applied Services : Part 2]
Azure Cognitive Services: Speech API's [Azure AI Applied Services : Part 3]
In this blog we discuss in detail the applications for Language API services with the help of flow charts and graphs to help you understand its application.It will help if the intent is clear what is it that you wish to achieve through analyzing conversations (Eg: Sentiment Analysis, Keyword-extraction, Language detection, etc)
Azure Cognitive Services provides with Speech API's and Language API's which often overlap with the functionalities they cater.
Speech API's - Assist in spoken language transformations
Language API's - Understand conversations and unstructured text
The key differentiation factor amongst the choice you make between the 2 is the use case intent. If you only wish to transform the format in either real-time or in batches its recommended to go with Speech services approach. If you wish to dig deeper insights in terms detailed analysis of either spoken or written languages (Transform+Analyze+Filter) its recommended to go with Language services approach.
Azure Cognitive Service for Language is a cloud-based service that provides Natural Language Processing (NLP) features for understanding and analyzing text. Use this service to help build intelligent applications using the web-based Language Studio, REST APIs, and client libraries.
Azure Language service provides several Natural Language Processing (NLP) features to understand and analyze text. Language service unifies Text Analytics, QnA Maker, and LUIS. These features can either be:
Features that can be implemented through LUIS and RestAPIs
Features that can be implemented through LUIS , RestAPIs & Docker Containers
(Note: For use case evaluation we have clubbed the features which can be deployed through LUIS & Rest API's under one section and the other which can be deployed with all 3 options : LUIS, RestAPI's and dockers. Off course since Azure keeps on integrating cognitive services with new functionalities please ensure you refer the reference links to be up to date with their implementations)
Language Service offerings all under one hood
Language Studio is a set of UI-based tools that lets you explore, build, and integrate features from Azure Cognitive Service for Language into your applications. Language Understanding (LUIS) is a cloud-based conversational AI service that applies custom machine-learning intelligence to a user's conversational, natural language text to predict overall meaning, and pull out relevant, detailed information. LUIS provides access through its custom portal, APIs and SDK client libraries.
Azure Cognitive Services provides with Speech API's and Language API's which often overlap with the functionalities they cater.
The Speech service includes the following application programming interfaces (APIs):
Where as Translator Service falling under Language API's provides Text-To-Text API's but this too involves language detection and conversion. Translator provides machine-based text translation in near real time. The service uses modern neural machine translation technology and offers statistical machine translation technology. Custom Translator is an extension of Translator, which allows you to build neural translation systems. The customized translation system can be used to translate text with Translator or Microsoft Speech Services.
QnA Maker is a cloud-based Natural Language Processing (NLP) service that allows you to create a natural conversational layer over your data. It is used to find the most appropriate answer for any input from your custom knowledge base (KB) of information. QnA Maker is commonly used to build conversational client applications, which include social media applications, chat bots, and speech-enabled desktop applications.
(Note: The QnA Maker service is being retired on the 31st of March, 2025. A newer version of the question and answering capability is now available as part of Azure Cognitive Service for Language. For question answering capabilities within the Language Service, see question answering)
Question answering provides cloud-based Natural Language Processing (NLP) that allows you to create a natural conversational layer over your data. It is used to find the most appropriate answer for any input from your custom knowledge base (KB) of information. Question answering is commonly used to build conversational client applications, which include social media applications, chat bots, and speech-enabled desktop applications. Several new features have been added including enhanced relevance using a deep learning ranker, precise answers, and end-to-end region support.
References
Feature References
Future Reads
Next Article : Azure Cognitive Services: Decision API's [Azure AI Applied Services : Part 5]
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Credit: Thanks Varma Gandhiraji, Nathan Widdup, Shweta Gaur for reviews and guidance
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