Text Analytics

Contains several NLP application cases for extracting data from text and speech. Many of these features are beneficial and are regularly employed while solving a business problem

Sentiment Prediction

Sentiment analysis is often performed on textual data to help businesses monitor brand and product sentiments from feedback, and understand customer needs.

SemanticText Similarity

Semantic similarity measures the similarity between items based on the likeness of their meaning or semantic content.

Text to Speech

Text-to-speech (TTS) is a type of assistive technology that reads digital text aloud.Text-to-Speech converts text input into audio data of natural human speech.

Sentence Summarizer

Summaryzer is an AI-based tool that helps summarize text articles extracting the most important sentences that provide an overview of the whole context.

PDF - Text Extractor

Analyze the input PDF document,extract the textual data and print the same.

Image - Text Extractor

Analyze the input image, extract the textual contents from the image and print the contents. Supported image formats include png, jpg and jpeg.

Form to Text

Analyze the input PDF Forms,extract the textual data including the checkboxes, and other options

String Matching

Two strings are compared and a similiarity score is calculated. String matching is the process of finding strings that match a given pattern.

NER Generation

Identify named entities in a text and classify them into pre-defined categories.

Audio Analytics

Analyze the input audio file and convert it into text using Artficial Intelligence

Text Clustering

Cluster text to gain an overall understanding of the text input from document

Word Cloud

Generates a wordcloud by setting sizes of words based on the count of occurence in input provided.

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