Instant Diacritics Restoration System for Sindhi Accent Prediction using N-Gram and Memory-Based Learning Approaches
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2017, Vol 8, Issue 4
Abstract
The script of Sindhi Language is highly complex due to many complexities including abundance of homographic words. The interpretation of the text turns so tough due to the possibility of multitudinal meanings associated with a homographic word unless given specific pronunciation with the help of diacritics. Diacritics help the readers to comprehend the text easily. Due to the rapidly developing nature of this era, people don’t bother writing diacritics in routine applications of life. Besides creating difficulties for human reading, the absence of diacritics does also make the text abstruse for machine reading. Relatively alike human, machines may also lead to semantic and syntactic complexities during computational processing of the language. Instant diacritics restoration is an approach emerged from the text prediction systems. This type of diacritics restoration is an unprecedented work in the realm of natural language processing, particularly in Indo-Aryan languages. A proposition for a framework using N-Grams and Memory-Based Learning approach is made in this work. The grab-point of this mechanism is its 99.03% accuracy on the corpus of Sindhi language during the experiments. The comparative edge of instant diacritics restoration is its being source of expedition in the performance of other natural language and speech processing applications. The future development of this approach seems vivid and clear for Sindhi orthography is highly similar to those of Arabic, Urdu, Persian and other languages based on this type of script.
Authors and Affiliations
Hidayatullah Shaikh, Javed Ahmed Mahar, Mumtaz Hussain Mahar
Keywords
Related Articles
- EP ID EP258319
- DOI 10.14569/IJACSA.2017.080422
- Views 87
- Downloads 0
Depth Limitation and Splitting Criteria Optimization on Random Forest for Efficient Human Activity Classification
Random Forest (RF) is known as one of the best classifiers in many fields. They are parallelizable, fast to train and to predict, robust to outlier, handle unbalanced data, have low bias, and moderate variance. Apart fro...
Performance Analysis of Faults Detection in Wind Turbine Generator Based on High-Resolution Frequency Estimation Methods
Electrical energy production based on wind power has become the most popular renewable resources in the recent years because it gets reliable clean energy with minimum cost. The major challenge for wind turbines is the e...
Optimization and Simulation Approach for Empty Containers Handling
Container handling problems at the container terminals are NP-hard problems. In this paper, we propose a new handling operation’s design and simulation of empty containers, taking into account the interrelated activities...
Breast Cancer Classification using Global Discriminate Features in Mammographic Images
Breast cancer has become a rapidly prevailing disease among women all over the world. In term of mortality, it is considered to be the second leading cause of death. Death risk can be reduced by early stage detection, f...
Review of Information Security Policy based on Content Coverage and Online Presentation in Higher Education
Policies are high-level statements that are equal to organizational law and drive the decision-making process within the organization. Information security policy is not easy to develop unless organizations clearly ident...