Improving accuracy of Part-of-Speech (POS) tagging using hidden markov model and morphological analysis for Myanmar Language

In Natural Language Processing (NLP), Word segmentation and Part-of-Speech (POS) tagging are fundamental tasks. The POS information is also necessary in NLP’s preprocessing work applications such as machine translation (MT), information retrieval (IR), etc. Currently, there are many research efforts in word segmentation and POS tagging developed separately with different methods to get high performance and accuracy. For Myanmar Language, there are also separate word segmentors and POS taggers based on statistical approaches such as Neural Network (NN) and Hidden Markov Models (HMMs). But, as the Myanmar language's complex morphological structure, the OOV problem still exists. To keep away from error and improve segmentation by utilizing POS data, segmentation and labeling should be possible at the same time.The main goal of developing POS tagger for any Language is to improve accuracy of tagging and remove ambiguity in sentences due to language structure. This paper focuses on developing word segmentation and Part-of- Speech (POS) Tagger for Myanmar Language. This paper presented the comparison of separate word segmentation and POS tagging with joint word segmentation and POS tagging

ミャンマー語テキストの形式手法による音節分割、正規化と辞書順排列

国立大学法人長岡技術科学大

Onsetsu hyoki no kyotsusei ni motozuita Ajia moji nyuryoku intafesu ni kansuru kenkyu

制度:新 ; 報告番号:甲3450号 ; 学位の種類:博士(国際情報通信学) ; 授与年月日:2011/10/26 ; 早大学位記番号:新577

Emotion detection on Myanmar texts

At this age, World Wide Web is growing faster. Many companies have built and launch social media networks. People so widely use social media to get the latest news, to express their emotions or moods, to communicate with their friends and so on. Emotions of social media users are needed to analyze in order to apply in many areas. Many researchers do research on emotion detection using different techniques with their languages. Currently, there are no emotion detection systems for Myanmar (Burmese) language. So, this paper describes the emotion detection system for Myanmar language. This system uses our pre-constructed M-Lexicon, a Myanmar word-emotion lexicon, in the detection process. This system detects six basic emotions such as happiness, sadness, anger, fear, surprise, and disgust. In order to determine certain emotion from the text, we also apply rule-based decision making on sentence nature. We use Facebook users’ status, which has been written in Myanmar words. Emotions of user groups are also summarized in this system. Our approach achieves 86% accuracy for emotion detection in Myanmar texts

Can an Accelerated Intervention Close the School Readiness Gap for Disadvantaged Children? An Evaluation of the Effects of the LEARN Project’s Summer Pre-Primary Program on Literacy Outcomes in Northern Lao PDR

Developed against the backdrop of Sustainable Development Goal 4, as well as a global trend towards rigorous assessment of early childhood programs, this thesis answers questions about the effects of an accelerated school readiness intervention for non-Lao children in disadvantaged communities of Lao People’s Democratic Republic. Through a longitudinal, cluster randomized control trial, the study employs multi-level regression with an analytical sample of 391 children to examine the outcomes of a summer pre-primary program piloted from 2015-2018 by the Lao government with support from Plan International and Save the Children International in the Dubai-Cares funded Lao Educational Access, Research, and Networking (LEARN) Project. Research questions are investigated through a design in which the same panel of children are assessed against a control group at three intervals using the Measurement of Development and Early Learning. The thesis identifies significant associations between receiving the treatment and achieving higher gain scores on several emergent literacy tasks between baseline and midline, with effects roughly in line with similar interventions in other contexts. At the same time, the thesis finds that those effects had largely faded by endline. An interaction between treatment and ethnicity was only evident in a few instances, suggesting that the intervention may have boosted school readiness for Khmu children more by the start of grade 1 and for Hmong children more during grade 1. The thesis raises important recommendations about how to improve the fit between the ultimate objectives of accelerated interventions, the evaluations they undergo, and the needs of the broader education system. New contributions to knowledge are also found by interrogating a global assessment paradigm through a comparative linguistic lens, so that forthcoming evaluations benefit from the lessons learned based on LEARN’s attempt to fit a square peg into a unique alpha-syllabic, tonal Southeast Asian language

Acoustic Modelling for Under-Resourced Languages

Automatic speech recognition systems have so far been developed only for very few languages out of the 4,000-7,000 existing ones. In this thesis we examine methods to rapidly create acoustic models in new, possibly under-resourced languages, in a time and cost effective manner. For this we examine the use of multilingual models, the application of articulatory features across languages, and the automatic discovery of word-like units in unwritten languages

RFID Technology in Intelligent Tracking Systems in Construction Waste Logistics Using Optimisation Techniques

Construction waste disposal is an urgent issue for protecting our environment. This paper proposes a waste management system and illustrates the work process using plasterboard waste as an example, which creates a hazardous gas when land filled with household waste, and for which the recycling rate is less than 10% in the UK. The proposed system integrates RFID technology, Rule-Based Reasoning, Ant Colony optimization and knowledge technology for auditing and tracking plasterboard waste, guiding the operation staff, arranging vehicles, schedule planning, and also provides evidence to verify its disposal. It h relies on RFID equipment for collecting logistical data and uses digital imaging equipment to give further evidence; the reasoning core in the third layer is responsible for generating schedules and route plans and guidance, and the last layer delivers the result to inform users. The paper firstly introduces the current plasterboard disposal situation and addresses the logistical problem that is now the main barrier to a higher recycling rate, followed by discussion of the proposed system in terms of both system level structure and process structure. And finally, an example scenario will be given to illustrate the system’s utilization