How can you generate text using Markov chains implemented with NLTK utilities

Question

With the help of Python programming, can you tell me how you can generate text using Markov chains implemented with NLTK utilities?

Answer 1

To generate text using Markov chains with NLTK utilities, you can create a simple Markov chain model based on n-grams, and then generate text by selecting the next word based on the previous word(s). Here is the code snippet you can refer to:

In the above code, we are using the following:

• Bigrams: Create bigrams from the text, representing pairs of consecutive words.
• Frequency Distribution: Calculate the frequency of each bigram to model the Markov chain.
• Text Generation: Start with a random word and generate the next word based on the bigram distribution, repeating the process to create a sequence of words.

The output of the above code would be:

Hence, this example generates text based on bigrams, where each word's generation depends on the preceding word. You can adjust the n-gram size and corpus to develop more complex text.