Natural language processing (NLP) is a branch of Artificial Intelligence that helps computers understand, interpret and synthesize human speech. It is seeking to reduce the gap in communication between a human and a computer.
Natural language processing includes many methods, such as static or exact methods. To create practical applications using NLP, a wide range of voice and text data are needed.
The main task of NLP includes the definition of language, semantic links, part-of-speech tagging, tokenization and parsing. This is similar to what students learn in the first years of schooling.
Tasks and methods
Using NLP, you can solve many applications, ranging from creating chatbots to analyzing huge text documents.
The main tasks of NLP include:
speech recognition
text analysis
text generation
text-to-speech
Speech recognition is the process of converting text files or voice to digital information. A simple example — when referring to Siri, a real-time algorithm recognizes the speech and converts it to the text.
Text analysis is the intellectual processing of many texts, the purpose of which is to identify patterns, patterns and similarities. It includes the extraction of information, search, analysis of statements, question-answer systems and the analysis of the tonality of the text.
Generating text is the process of creating texts using computer algorithms.
Text-to-speech is the reverse process of speech recognition. An example is the reading of information from the Internet by voice assistants.
Where is it used?
There are many ways to use NLP technologies in everyday life. In addition, using voice assistants such as Alexa or Cortana, it can be, for example:
email services use Bayesian spam filtering, a statistical method of NLP that compares incoming messages with a spam database and identifies unwanted mails.
text editors such as Microsoft Word or Google Docs use NLP to correct errors in words, not only grammatical, but also based on the context of the sentence.
virtual keyboards in modern smartphones with NLP can anticipate subsequent words in the context of a sentence.
What Hey Machine Learning do?
Hey Machine Learning uses existing NLP tools to solve business problems. One of such tasks was the creation of a chatbot for a travel agency.
Often, the managers of the travel agency do not have time to process all inquiries from customers, especially during non-working hours. Partly solve of this problem could chatbots.
Engineers of our company have developed a multi-platform chatbot that can conduct live conversation, collect applications for tours and answer frequently asked questions. Customers, in turn, receive instant answers.
The chatbot was created using LSTM Recurrent neural network and Dialogflow framework for constructing natural dialogues.
As a result, company managers can more effectively use the working time and process those applications for tours, which the client has already confirmed. For users, in turn, the waiting time for the manager's response decreases, which positively affects the company's service and reputation.
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