Question

In: Computer Science

Explain/demonstrate how to use NLTK to train a language model to predict a word's language given...

Explain/demonstrate how to use NLTK to train a language model to predict a word's language given a limited training set of unigram, bigram, and trigram character sets.

Expert Solution

Hi,

NLTK stands for Natural Language Tool Kit,it is written in python programming language and is a suite of programs for symbolic and statistical natural language processing.Natural Language processing(NLP) enables the computer to interact with humans in a natural manner.It helps the computer to understand the human language and derive meaning from it.

NLTK is called as the wonderful tool for teaching , and working in computational linquistics using python and an amazing library to play with natural language.

Lets describe how NLTK is used to train a language model to predict a words language in this three character set.

1: Unigram:

In unigram each individual word is considered as a token.Using NLTK

1. import nltk

2.From nltk.corpus import brown (from brown corpus statistics on words are derived )

3.words=brown.words()

4 .fdist=nltk.FreqDist(w.lower() for w in words)

5. total=0

6: for word in fdist : total+= fdist [word]

2: Bigrams:

In bigrams a pair of 2 words are considered as a token. Using NLTK

1: Import nltk

2: bigrams=nltk.bigrams(words)

3:cfd= nltk.ConditionalFreqDist(bigrams)

3: Trigrams

In trigrams 3 words are taken as token.Using NLTK,

1: import nltk

2: from nltk import word tokenize

3:from nltk . util import ngrams

4:token = nltk.word_tokenize(text1) (the text is tokenized)

5: trigrams=ngrams(token,3) (find all trigrams in the text1)

6: trigrams

Hope you help this...

Thank you....

venereology answered 1 month ago

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