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Seminar Presentation of Speech Application Language Tags

Seminar Presentation of Speech Application Language Tags

Project / Seminar Material
Reference ID: PS-25413-TM

DEDICATION

This research material titled “Seminar Presentation of Speech Application Language Tags” is dedicated to God for his enabling grace, and to all computer enthusiasts who contributed to make life a pleasant experience during my research documentation.

ACKNOWLEDGEMENT

I extend my sincere gratitude to all those who contributed to the completion of this project. Special thanks to my Supervisor (Name of your Supervisor), the Head of Department (Name of your HOD), the Lecturers in the department of Computer Science Education, Book Authors and Profound Scholars of existing or related project material on “Seminar Presentation of Speech Application Language Tags” for their invaluable guidance, support, and expertise throughout the journey.

I am also grateful to your study area (mention any funding organizations, if applicable) for their financial assistance. This research would not have been possible without the encouragement and assistance of some stakeholders (mention any mentors, teachers, or colleagues). Additionally, I would like to acknowledge the understanding and patience of my family and friends during this endeavor. Your unwavering support has been a constant source of motivation. Thank you all for being part of this meaningful endeavor.


Seminar Presentation of Speech Application Language Tags

CHAPTER ONE

1.1 Introduction

Tagging defines an association. POS tagging tags Part-Of-Speech labels for a token in any language structure. POS is immensely used in text mining and it is an unsupervised/supervised classification. If a tagger is supervised then it counts the number of labeled set of data whose efficiency relies on the existence of the tagging dictionary. On the other hand unsupervised tagging seems to be a reasonable solution because they use un-annotated language models. Part of speech (POS) tagging is the process of assigning a POS or other lexical class marker to each word in a language texts according to their respective POS label according to its definition and context (Chungku et al., 2010; Onyenwe, 2017). It is an important enabling task for NLP applications such as a preprocessing step to syntactic parsing, information extraction and retrieval, statistical machine translation, corpus linguistics, etc.

As a prelude to other parts of this study, this chapter will discuss the background upon which this study was initiated, the statement of problems that led to this study, the Aim and Objectives of the study. Others are Significance of the study, Scope of work, Research hypothesis and questions, Limitations of the Study and Definition of technical terms.

CHAPTER TWO

2.0 Literature Review

2.1 Introduction

This chapter focuses on the review of related literature. A literature review includes the current knowledge as well as theoretical and methodological contributions to a particular topic. It documents the state of the art with respect to the topic you are writing. It surveys the literature in the topic selected. In this research work the literature review includes the …

Summary Headlines for Seminar Presentation of Speech Application Language Tags



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