Tagging an accurate grammar to the specific phrase in sentences could be very crucial undertaking for specific Indian languages. Part of speech tagging is a fundamental manner for one of a kind natural language processing applications like machine translation, speech Recognition etc. Part Of Speech is used for assigning tag the usage of the grammatical statistics of every word of a sentence. We have used statistical approach like Hidden Markov Model (HMM) and rule based method to investigate the accuracy of a part of speech tagger for Guajarati language. In the paper we discussed available tagging strategies for numerous Indian languages. Further we discussed proposed approached with the use of BIS tag set that includes 11 fundamental tags and more than 25 sub tags. Further we practice HMM model for Sports and amusement information set, we are getting accuracy 70% and 56% respectively. After applying rule based approach we achieved 76% accuracy for sports activities and 80% for Entertainment dataset. After that we have used leisure information set with 95614 phrases and we were given 52% accuracy with hmm and 83 % accuracy with the aid of after making use of rules with hmm.
CITATION STYLE
Bhatt, P. M., & Ganatra, A. (2019). Analyzing & enhancing accuracy of part of speech tagger with the usage of mixed approaches for Gujarati. International Journal of Recent Technology and Engineering, 8(1), 3077–3086.
Mendeley helps you to discover research relevant for your work.