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Microsoft added Hindi to its Text Analytics service to help businesses strengthen customer support. Pixabay

Microsoft on Thursday said it has added Hindi Feature to its Text Analytics service to help businesses strengthen customer support through a complete analysis of user perception and feedback in the most widely spoken language in India.

Text Analytics is part of the Microsoft Azure Cognitive Services.


The functionality provided by Text Analytics includes sentiment analysis, opinion mining, key phrase extraction, language detection, named entity recognition, and Personally Identifiable Information (PII) detection.

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Using this service, organizations can find out what people think of their brand or topic as this enables analyzing Hindi text for clues about positive, neutral, or negative sentiment.

The Hindi Text Analytics service can be used for any textual / audio input or feedback in combination with Azure Speech-to-Text service, Microsoft 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,” Sundar Srinivasan — General Manager — AI & Search — Microsoft India, said in a statement.


The Text Analytics service can be used for any textual / audio input or feedback. Pixabay

“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.”

Microsoft’s Text Analytics feature uses AI models to analyze content in Hindi, using Natural Language Processing (NLP) for text mining and text analysis.

Its 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.

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The service also provides sentiment labels (such as “negative”, “neutral” and “positive”) based on the highest confidence score at a sentence and document-level.

“This helps brands in detecting positive and negative tonality in customer reviews, social media and call center conversations, and forum discussions, among other channels no matter where their data resides,” said the company. (IANS)


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