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Microsoft Adds Hindi To Its Text Analytics Service To Strengthen Sentiment Analysis Support

Today, Microsoft has announced the addition of Hindi as the latest language under its Text Analytics service to support businesses and organisations with customer Sentiment Analysis. 

Microsoft’s Text Analytics is part of the Microsoft Azure Cognitive Services. The service is powered by Microsoft Azure and uses the latest AI models to analyse content in Hindi, using Natural Language Processing (NLP) for text mining and text analysis.


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Using this service, organisations can find out what people think of their brand or topic as this enables analysing Hindi text for clues about positive, neutral, or negative sentiment. The functionality provided by Text Analytics includes sentiment analysis, opinion mining, key phrase extraction, language detection, named entity recognition, and PII detection. Sentiment analysis currently supports more than 20 languages including Hindi.  

The Text Analytics service can be used for any textual / audio input or feedback in combination with Azure Speech-to-Text service. This new development enables Sentiment Analysis for the most spoken language in India and the fourth most spoken language in the world.   

Sundar Srinivasan, General Manager, AI & Search at Microsoft India said, “Underlining our commitment to helping empower every business to achieve more, Microsoft has added Hindi to the already robust set of international languages supported by Text Analytics service. We are helping brands break language barriers and reach out to Hindi-speaking customers to understand the customer’s sentiment about their products, services, and broaden their user feedback reach. With this release, we are bringing in cutting edge cloud services, AI, and natural language processing to deepen the trust between brands and customers in India.” 

Microsoft Text Analytics service’s Sentiment Analysis feature evaluates the text and returns confidence scores between 0 and 1 for positive, neutral, and negative sentiment for each document and sentences within a document. The service also provides sentiment labels (such as “negative”, “neutral” and “positive”) based on the highest confidence score at a sentence and document-level. 

It can be accessed from the Azure cloud and on-prem using Containers. This helps brands in detecting positive and negative tonality in customer reviews, social media & call centre conversations, and forum discussions, among other channels no matter where their data resides.   

The Sentiment Analysis feature provides more granular information about the opinions related to aspects (such as the attributes of products or services from a brand) in text. Businesses can extract insights from customer service calls by using Speech-to-Text, Sentiment Analysis, and Key Phrase Extraction in a single workflow.

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Ambika Choudhury
A Technical Journalist who loves writing about Machine Learning and Artificial Intelligence. A lover of music, writing and learning something out of the box.

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