Self-study|IT|Int|Lesson 8: Natural Language Processing

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Type what these abbreviations stand for


Match the IT terms with their definitions


💡Today we’re going to talk about another branch of Artificial Intelligence, which is Natural Language Processing, and we’re going to learn how machines can interact with people.

Ready? Let’s get started!

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Answer the questions using your own ideas

1. How does NLP work?

2. What are the techniques used in NLP?


Read the text about NLP and mark the sentences as True or False

Natural language processing

Natural language processing (NLP) is a form of AI that extracts meaning from the human language to make decisions based on the information.

How does NLP work?

NLP involves applying algorithms to identify and extract the natural language rules such that the unstructured language data is converted into a form that computers can understand. When the text has been provided, the computer will utilize algorithms to extract meaning associated with every sentence and collect the essential data from them. Sometimes, the computer may fail to understand the meaning of a sentence well, leading to obscure results.

For example, a humorous incident occurred in the 1950s during the translation of some words between the English and the Russian languages.

Here is the biblical sentence that required translation:

«The spirit is willing, but the flesh is weak.»

Here is the result after the sentence was translated to Russian and then back to English:

«The vodka is good, but the meat is rotten.»

What are the techniques used in NLP?

Syntactic analysis and semantic analysis are the main techniques used to complete Natural Language Processing tasks.

Syntax refers to the arrangement of words in a sentence such that they make grammatical sense. In NLP, syntactic analysis is used to assess how the natural language aligns with the grammatical rules. Computer algorithms are used to apply grammatical rules to a group of words and derive meaning from them.

Semantics refers to the meaning that is conveyed by a text. Semantic analysis is one of the difficult aspects of Natural Language Processing that has not been fully resolved yet. It involves applying computer algorithms to understand the meaning and interpretation of words and how sentences are structured.

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Look at the list of NLP limitations and guess what they imply

In general, NLP faces the following challenges:

  • physical limitations;
  • no unifying semantic repository;
  • current information retrieval systems.

Read the descriptions of the three limitations and choose the correct heading for each of them

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Choose the correctly spelled words


Read the task and provide information about NLP. Use the phrases from the first exercise

Imagine that a local university has invited you to deliver a guest lecture about NLP. The university staff sent you some questions you should cover.

  • What is NLP?
  • How does NLP work?
  • What are the techniques used in NLP?
  • What are some limitations of NLP?

Use the voice recorder.

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Listen about some other applications of NLP and choose the ones mentioned

NLP is still evolving, but there are already many incredible ways it is used today. Here are some applications of natural language processing.

1. Email assistant. Autocorrect, grammar and spell check, as well as autocomplete, are all functions enabled by NLP. The spam filter on your email system uses NLP to determine what emails you’d like to keep in your inbox and what are likely spam and should be sorted out.

2. Drives e-commerce. NLP allows for better search results when you shop online. It is becoming adept at deciphering the intent of your message even if there are spelling errors or important details you omit in your search terms.

3. Another use is translation software, for example, Google Translate that is used by 500 million people every day to understand more than 100 world languages. Another example is SignAll, which recognizes and translates sign language. This helps individuals who are deaf communicate with those who don’t know sign language.

4. Natural language processing technology is even being applied for aircraft maintenance. Not only could it help mechanics synthesize information from enormous aircraft manuals, it can also find meaning in the descriptions of problems reported verbally or handwritten from pilots and other humans.

5. There’s even work being done to have natural language processing assist with predictive police work to specifically identify the motive in crimes.



Listen to the audio again and describe some benefits of the NLP applications. You can make notes to use for your description

NLP is still evolving, but there are already many incredible ways it is used today. Here are some applications of natural language processing.

1. Email assistant. Autocorrect, grammar and spell check, as well as autocomplete, are all functions enabled by NLP. The spam filter on your email system uses NLP to determine what emails you’d like to keep in your inbox and what are likely spam and should be sorted out.

2. Drives e-commerce. NLP allows for better search results when you shop online. It is becoming adept at deciphering the intent of your message even if there are spelling errors or important details you omit in your search terms.

3. Another use is translation software, for example, Google Translate that is used by 500 million people every day to understand more than 100 world languages. Another example is SignAll, which recognizes and translates sign language. This helps individuals who are deaf communicate with those who don’t know sign language.

4. Natural language processing technology is even being applied for aircraft maintenance. Not only could it help mechanics synthesize information from enormous aircraft manuals, it can also find meaning in the descriptions of problems reported verbally or handwritten from pilots and other humans.

5. There’s even work being done to have natural language processing assist with predictive police work to specifically identify the motive in crimes.


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Complete the collocations with words given


Read the task and talk about NLP in your daily life. Use the phrases from the first exercise

Think about some apps, software, services with NLP that you use in your daily life and then explain how they make your life or work better or worse. You can find some ideas 🔗here.

Steps:

  • Plan what you are going to say.
  • Make some notes in the text area below.
  • Present your ideas.

Use the voice recorder.


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Think over these questions:

  • To what extent did you find the topic of this lesson interesting? Why?
  • What new words or phrases can you recall now?
  • Would you like to use more NLP-based tools in the future? Why (not)?

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Complete the summary of the article you read in the lesson with the words given below


Match the words to their definitions. It will help you to read the article about the future of NLP


Read the text about the current and future applications of NLP and complete the statements

Future trends of natural language processing

NLP, one of the most exciting components of AI, is all set to rule the way we communicate with the external world. NLP uses computational and mathematical methods to analyze the human language and to facilitate interactions with computers using conversational language. Subtopics in this genre include natural language understanding of the inputs created by humans, and natural language generation, to focus on generating natural language narratives.

NLP is the voice behind Siri and Alexa, likewise customer service chatbots use the power of NLP to drive customized responses in e-commerce, healthcare and business utilities. Some of the more omnipresent applications of NLP today include virtual assistants, sentiment analysis, customer service and translation.

As technology continues to grow and evolve, the future application of NLP will be more user-oriented. For example, virtual assistants will be able to answer a lot more complicated questions assessing the implications along with the literal meaning of the question asked. (Q: How is the weather today? A: Rainy, you will need an umbrella). In the future times to come, businesses will be able to offer a lot of professional customer services, take calls instantly and escalate problems to real people.

The application of NLP is not restricted to solving customer queries or providing customized shopping or health advice but has evolved into more technological assistance of sorts. In the current times, NLP can be trained to provide a list of errors if one uses NLP to ask «what is wrong with my network?» In the future, NLP will be able to understand the user’s real intent: he wants his network fixed for access. The future with NLP is exciting as advances in NLP will allow mankind to shift focus from the questions to the results. It will be a giant leap when NLP is able to understand the user’s input and provide more complex solutions answering the user’s true intent.

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Match the questions about VR and AR to the corresponding answers


Watch the video about shopping with augmented reality and then mark the sentences as True or False


Урок Homework Курс
  • What do they stand for?
  • NLP
  • NLP limitations
  • NLP overview
  • NLP applications
  • NLP in your life
  • Homework 1
  • Homework 2