Mizo language is a tonal language in which the tone, pitch, and contour of the syllables can change the meanings of a word. In addition, the two missionaries developed the first Lushai grammar and dictionary, which served as the foundation for the Mizo language and literature to be developed in the following decades. They believed that the Roman script was more appropriate for the Mizo language. Before crafting the Mizo alphabet, a thorough comparison was made to determine which Indian scripts, such as Hindi and Bengali, and the Roman script, should be used as the foundation of the alphabet. The two missionaries started the work on developing the Mizo alphabet, and it was completed on the 1st of April, 1894. Frederic William Savidge (Sap Upa), in Mizoram in 1894. There was no text writing system for the Mizo language until the arrival of two pioneer Christian missionaries, James Herbert Lorrain (Pu Buanga) and Dr. Aside from Mizoram's mainland, this language is also spoken in the surrounding states such as Tripura, Assam, Manipur, Meghalaya, Nagaland, and lesser parts of Myanmar and Bangladesh. It is the primary and most widely spoken language in Mizoram, a state in northeastern India. Mizo language is classified under the Tibeto-Burman language family. Many natural language processing activities and applications, including speech synthesis and recognition, parsing, machine translation, and information extraction, rely significantly on it. Although POS tagging is not effective in and of itself, it is widely acknowledged as the first step in comprehending a natural language. However, a high degree of accuracy can be obtained, which can be used for practical purposes. Till date, there is currently no known solution that can answer the part of speech tagging problem with 100% accuracy in any language, including English. Since the only information we have at the POS tagging phase is word-level information such as morphological information, a POS tagging cannot be expected to be 100% correct. A completely correct POS tagging would require other information such as syntax, semantics, and world knowledge. Resolving ambiguity is a major challenge of POS tagging since, by nature, most words have multiple senses. Different POS tagging models, therefore, need to be studied and evaluated to determine their suitability for a language under consideration. The performance of a POS tagger directly determines the quality and reliability of subsequent phases of NLP tasks. ![]() A POS tagger accepts a sequence of text in a particular language as input, and the tagger assigns the appropriate tag to each word in the sequence. ![]() The rapid advance in the field of NLP and more and more of its usage being integrated into our daily lives compels one to harness its promising potential.įor many natural language processing tasks, a reliable POS tagger is a prerequisite. ![]() It is a sub-field of Artificial Intelligence (AI) that aims to facilize natural communication with computers. The task of using computer programs to process natural languages in their written or oral forms in order to extract meaningful information is known as natural language processing (NLP).
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