PARTS OF SPEECH TAGGING USING VITERBI ALGORITHM

PARTS OF SPEECH TAGGING USING VITERBI ALGORITHM

G Venkata Vaibhav1, N Abhishek Vardhan2, Ch Surendhar Reddy3, B Yashwanth Kumar4,

M Kranthi Kiran5.

1,2,3,4Student, Department of Computer Science Engineering, Gitam University ,Visakhapatnam.

5Assistant Professor, Department of Computer Science Engineering, Gitam University ,Visakhapatnam.

Abstract

Preprocessing words and phrases are required for each NLP activity since it facilitates subsequent work.

POS tagging is becoming increasingly popular these days. Text to speech, syntactic analysis, and machine translation all benefit from POS tagging, which is an effective form of preprocessing tagging. When it comes to POS taggers, they must be well-versed on the term. It is accessible to humans because describing it is simple. However, if the number of words is increased to a million, users will be unable to complete the POS tag. We present the Viterbi method in this study to assist computers in tagging lexical categories more effectively. The Viterbi algorithm use dynamic programming to solve problems. As we all know, the word is quite sensitive to its placement. The word's POS is connected to the words around it. We run simulations to see how Viterbi Algorithms operate in POS taggers and calculate accuracy