Statistical Machine Translation between Myanmar Sign Language and Myanmar Written Text

This paper contributes the first evaluation of the quality of automatic translation between Myanmar sign language (MSL) and Myanmar written text, in both directions. Our developing MSL-Myanmar parallel corpus was used for translations and the experiments were carried out using three different statistical machine translation (SMT) approaches: phrase-based, hierarchical phrase-based, and the operation sequence model. In addition, three different segmentation schemes were studies, these were syllable segmentation, word segmentation and sign unit based word segmentation. The results show that the highest quality machine translation was attained with syllable segmentations for both MSL and Myanmar written text

Development of Natural Language Processing based Communication and Educational Assisted Systems for the People with Hearing Disability in Myanmar

Information and communication technologies (ICTs) provide people with disabilities to better integrate socially and economically into their communities by supporting access to information and knowledge, learning and teaching situations, personal communication and interaction. Our research purpose is to develop systems that will provide communication and educational assistance to persons with hearing disability using Natural Language Processing (NLP). In this paper, we present corpus building for Myanmar sign language (MSL), Machine Translation (MT) between MSL, Myanmar written text (MWT) and Myanmar SignWriting (MSW) and two Fingerspelling keyboard layouts for Myanmar SignWriting. We believe that the outcome of this research is useful for educational contents and communication between hearing disability and general people

Sign Language Recognition for Myanmar Number Using Three Different SVM

People who are affected by hearing problems use a communication method called Sign Language. Sign Language differs from region to region, country to country and continent to continent. Machine learning can play a significant role in impacting lives of the hearing-impaired people and can help them to communicate with their environments more easily. This paper presents a very simple and efficient approach for Myanmar Sign Language (MSL) recognition system which is capable of recognizing the static hand gesture images that represent the Myanmar numbers from zero to ten. The main objective of this paper is to investigate the performance of three different Support Vector Machine (SVM) classifiers for Myanmar number sign recognition. The proposed system contains three stages, namely, pre-processing, feature extraction and classification. In the feature extraction stage, different features are extracted using Scale Invariant Feature Transform (SIFT) algorithm. In the classification stage, three different SVM classifiers (SVCs); SVC with linear kernel, SVC with polynomial kernel and LinearSVC are tested and evaluated. Among these three classifiers, SVC with polynomial kernel yielded the highest accuracy score with 87%. Although there are some limitations in the datasets, each classifier provides the encouraging results

Variation and Segregation in F2 Population of Hot Pepper (Capsicum annuum)

The experiment was carried out to investigate variations in quantitative traits and segregation pattern for some qualitative traits of selected F2 hot pepper. The seeds were collected from 23 F1 hot pepper plants grown at Yezin Agricultural University Farm. The experiment was laid out in a Randomized Complete Block design (RCBD) with two replications. Leaf length, leaf width, filament length, corolla length, fruit width, thousand seed weight and number of seeds per pod showed important contributors towards total variation among the genotypes. Variability study on these seven traits highlighted that phenotypic component was the major contributor to total variance. Low and medium heritability values and higher phenotypic coefficient of variation (PCV) suggested that all the above phenotypic traits interacted with the environment rather than genetic variation. Segregation patterns of 21 qualitative traits indicated similar characters for angled stem, erect flower, white corolla and corolla spot, rotate corolla, white filament, elongate fruit, obtuseness of fruit at pedicel attachment and absence of neck at the base of fruit. Segregation distortions observed in some traits: nodal anthocyanin, branching habit, leaf shape, mature fruit color suggested that they are polygenic traits. Calyx margin and fruit bearing characters followed the Mendelian ratio (3:1), highlighting the monogenic recessive nature of the gene. Anther color expressed independent assortment with complete dominance (9:3:3:1). Plant growth habit, stigma exsertion, fruit surface, leaf color and male sterility resulted as modified F2 dihybrid ratios indicating the involvement of two genes controlling each trait. From the breeding point of view, variation in quantitative traits, on which environmental factors have a profound effect, may hinder the progress in selection for progeny containing favorable genes. However, variation in qualitative traits as a result of segregation in F2 progeny might be useful for selection of desirable quality in next generation

Transfer Learning Based Myanmar Sign Language Recognition for Myanmar Consonants

Abstract— In this paper, a study on the different Transfer Learning models is made for the purpose of recognizing Myanmar Fingerspelling (Myanmar Sign Language) alphabets. This experiment shows that Transfer Learning can play a significant role for sign language recognition system and is capable of recognizing the static hand gesture images that represent the Myanmar consonants from က (ka) to အ (a). The main objective of this paper is to investigate the performance of various Transfer Learning models for Myanmar Fingerspelling recognition. We proposed 12 Transfer Learning models using TensorFlow library and the accuracy for each model is compared. Among these 12 models, VGG16, ResNet50 and MobileNet with epoch 50 yielded the highest accuracy score with 94%. Although there are some limitations in the datasets, each model provides the encouraging results and thus, it can believe that the fully generalizable recognition system based on Transfer Learning can be produced for all Myanmar Sign Language Fingerspelling characters by doing further research with more data

Two Fingerspelling Keyboard Layouts for Myanmar SignWriting

Sign language is the first language for the Deaf. The Deaf people could communicate with the hearing people by Sign language. The use of sign language technologies in the interface of computing systems to improve their accessibility for deaf signers. In this paper, we propose two fingerspelling keyboard layouts for typing Myanmar fingerspelling characters with SignWriting. Fingerspelling is used in sign language to spell out names of people and places for which there is not a sign. We discuss the usability of our approach based on the user study and the evaluation results. The evaluations were made in terms of typing speed CPM (Character per Minute) and Likert scale feedbacks from both hearing-impaired and hearing users. The outcome of the research will be useful in implementing Myanmar SignWriting text input interface for Myanmar sign language

Serological evidence indicates widespread distribution of rickettsioses in Myanmar

Background Little research has been published on the prevalence of rickettsial infections in Myanmar. This study determined the seroprevalence of immunoglobulin G (IgG) antibodies to rickettsial species in different regions of Myanmar. Methods Seven hundred leftover blood samples from patients of all ages in primary care clinics and hospitals in seven regions of Myanmar were collected. Samples were screened for scrub typhus group (STG), typhus group (TG) and spotted fever group (SFG) IgG antibodies using enzyme-linked immunosorbent assays (ELISA). Immunofluorescence assays were performed for the same rickettsial groups to confirm seropositivity if ELISA optical density ≥0.5. Results Overall IgG seroprevalence was 19% [95% confidence interval (CI) 16–22%] for STG, 5% (95% CI 3–7%) for TG and 3% (95% CI: 2–5%) for SFG. The seroprevalence of STG was particularly high in northern and central Myanmar (59% and 19–33%, respectively). Increasing age was associated with higher odds of STG and TG seropositivity [per 10-year increase, adjusted odds ratio estimate 1.68 (p < 0.01) and 1.24 (p = 0.03), respectively]. Conclusion Rickettsial infections are widespread in Myanmar, with particularly high seroprevalence of STG IgG antibodies in central and northern regions. Healthcare workers should consider rickettsial infections as common causes of fever in Myanmar