Cloudmersive NLP Connector Decodes Human Language
Cloudmersive NLP language translator helps users extract the meaning of text using deep learning and neural natural language processing (NLP).
If that sounds a little next world to you, consider that speech recognition is an important component of both smart home technologies and synthesized human voices from Siri, Alexa and a growing number of customer service call centers that we hear daily but often take for granted. Deep learning technologies can not only identify language, but by breaking down characters and word groups can predict probable surrounding speech that leads to full translation.
Cloudmersive NLP connector can translate input Russian or German sentences into English, or the opposite converting English into Russian or German. But, it goes farther. It can paraphrase or rephrase up to ten possible rephrasings of the original sentence. And, it will analyze text for subjectivity and objectivity (and how much of either exists), perform sentiment analysis and classification of text as positive, negative, or neutral, or determine whether the input contains profane or obscene language.
What we’re talking about here is machine understanding of what we say, whether we’re being sarcastic or serious and if we’re off color in our expression. Powerful.
Cloudmersive NLP connector can also automatically determine the language in which a text string is written from its bank of 14 languages including: Chinese, Danish, Dutch, English, French, German, Italian, Japanese, Korean, Norwegian, Portuguese, Russian, Spanish, or Swedish.
It can get component words in an input string, extract sentences or entities from a string, or check whether the sentence is spelled correctly and find spelling correction suggestions returning the result in JSON.
Wondering how to best use this connector? This could be an important tool to properly route support issues quickly and efficiently. Rather than using the expensive sentiment detection capabilities of Microsoft AI, you could use this connector to route tweets, emails, or other incoming data to the appropriate channels.
- Support receives an email with negative sentiment. Use Power Automate with Cloudmersive NLP to highlight the proper support person to address the issue.
- Keep the human element of decision within your team. Use the connector to translate all incoming support messages into English for internal staff to route.
- Streamline outgoing tweets. Automatically translate tweets generated from one account by a single marketing person in their native tongue into multi-lingual tweets posted through other company accounts. to distribute it worldwide.
I’d argue that understanding communication is the key to building solid business relationships and having a connector that can harness the use of machine learning for language translation makes it an invaluable tool for Power Automate users. We’d love to know how you are using Power Automate connectors and urge you to talk to us about your successful projects or ones where you may be struggling. We rescue apps. Tell us about your Power Automate connector.
* In linguistics, “The Penn Treebank, in its eight years of operation (1989-1996), produced approximately 7 million words of part-of-speech tagged text, 3 million words of skeletally parsed text, over 2 million words of text parsed for predicate argument structure, and 1.6 million words of transcribed spoken text annotated for speech disfluencies.” ~ Taylor, Marcus and Santorini The Penn Treebank: An Overview.