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

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

Prevalence, antimicrobial resistance and genomic comparison of non-typhoidal salmonella isolated from pig farms with different levels of intensification in Yangon Region, Myanmar

In Myanmar, where backyard, semi-intensive, and intensive pig (Sus scrofa domesticus) farming coexist, there is limited understanding of the zoonotic risks and antimicrobial resistance (AMR) associated with these farming practices. This study was conducted to investigate the prevalence, AMR and genomic features of Salmonella in pig farms in the Yangon region and the impact of farm intensification to provide evidence to support risk-based future management approaches. Twenty-three farms with different production scales were sampled for two periods with three sampling-visit each. Antimicrobial susceptibility tests and whole-genome sequencing were performed on the isolates. The prevalence of Salmonella was 44.5% in samples collected from backyard farms, followed by intensive (39.5%) and semi-intensive farms (19.5%). The prevalence of multi-drug resistant isolates from intensive farms (45/84, 53.6%) was higher than those from backyard (32/171, 18.7%) and semi-intensive farms (25/161, 15.5%). Among 28 different serovars identified, S. Weltevreden (40; 14.5%), S. Kentucky (38; 13.8%), S. Stanley (35, 12.7%), S. Typhimurium (22; 8.0%) and S. Brancaster (20; 7.3%) were the most prevalent serovars and accounted for 56.3% of the genome sequenced strains. The diversity of Salmonella serovars was highest in semi-intensive and backyard farms (21 and 19 different serovars, respectively). The high prevalence of globally emerging S. Kentucky ST198 was detected on backyard farms. The invasive-infection linked typhoid-toxin gene (cdtB) was found in the backyard farm isolated S. Typhimurium, relatively enriched in virulence and AMR genes, presented an important target for future surveillance. While intensification, in terms of semi-intensive versus backyard production, maybe a mitigator for zoonotic risk through a lower prevalence of Salmonella, intensive production appears to enhance AMR-associated risks. Therefore, it remains crucial to closely monitor the AMR and virulence potential of this pathogen at all scales of production. The results underscored the complex relationship between intensification of animal production and the prevalence, diversity and AMR of Salmonella from pig farms in Myanmar

Evaluation of Diagnosis according to Myanmar Traditional Medicine by using Expectation Maximization

Nowadays, computer based medical system is playing a role in assisting both diagnosis and treatment. Thus, this system intends to provide information for junior traditional medicine practitioners and user who interested traditional medicine. Before evaluating, this system stores the knowledge of traditional medical experts and medical records from previous cases as training database. And, it produces the generate rules from training data set by using Naïve Bayesian Classifier. When user inputs symptoms, this system analyzes corrected diagnosis and suitable dosage. If user inputted symptoms are not evolved by NB classification, we use Expectation Maximization (EM) step that computes maximum likelihood estimation of unlabeled data. This EM step probabilistically evaluates unlabeled data by using available labeled data which is training by NB. As a result, in this paper, we evaluate corrected diagnosis and proper dosage by using semisupervised learning method (EM with NB classification) in order to improve correctness of classifier

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

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

Resumo: As tecnologias da informação e comunicação (TICs) fornecem às pessoas com deficiência uma melhor integração, tanto social quanto economicamente, em suas comunidades, apoiando-os no acesso à informação e ao conhecimento, situações de ensino-aprendizagem, comunicação pessoal e interação. Nosso objetivo com esse trabalho tem sido desenvolver sistemas que proporcionem aos surdos meios que lhes permitam se comunicar com maior fluidez e ao mesmo tempo receberem assistência educacional adequada, usando o Processamento de linguagem natural (PNL). Neste artigo, apresentamos o corpus para a linguagem de sinais de Mianmar (MSL), um sistema de Tradução de Máquina (MT) entre a língua de sinais de Mianmar (MSL), o texto escrito em Mianmar (MWT) e Myanmar SignWriting (MSW), dois layouts de teclado para uso com o sistema Mianmar SignWriting, desenvolvimento de um dicionário para MSL, além de um sistema de classificação “Myanmar Fingerspelling Image”. Acreditamos que o resultado desta pesquisa é útil não apenas para fins educacionais, mas também para o estabelecimento de uma melhor interface entre surdos e ouvintes

Preliminary monitoring of concentration of particulate matter (PM2.5) in seven townships of Yangon City, Myanmar

Abstract Background Airborne particulate pollution is more critical in the developing world than in the developed countries in which industrialization and urbanization are rapidly increased. Yangon, a second capital of Myanmar, is a highly congested and densely populated city. Yet, there is limited study which assesses particulate matter (PM2.5) in Yangon currently. Few previous local studies were performed to assess particulate air pollution but most results were concerned PM10 alone using fixed monitoring. Therefore, the present study aimed to assess distribution of PM2.5 in different townships of Yangon, Myanmar. This is the first study to quantify the regional distribution of PM2.5 in Yangon City. Methods The concentration of PM2.5 was measured using Pocket PM2.5 Sensor (Yaguchi Electric Co., Ltd., Miyagi, Japan) three times (7:00 h, 13:00 h, 19:00 h) for 15 min per day for 5 days from January 25th to 29th in seven townships. Detailed information of eight tracks for PM2.5 pollution status in different areas with different conditions within Kamayut Township were also collected. Results The results showed that in all townships, the highest PM2.5 concentrations in the morning followed by the evening and the lowest concentrations in the afternoon were observed. Among the seven townships, Hlaingtharyar Township had the highest concentrations (164 ± 52 μg/m3) in the morning and (100 ± 35 μg/m3) in the evening. Data from eight tracks in Kamayut Township also indicated that PM2.5 concentrations varied between different areas and conditions of the same township at the same time. Conclusion Myanmar is one of the few countries that still have to establish national air quality standards. The results obtained from this study are useful for the better understanding of the nature of air pollution linked to PM2.5. Moreover, the sensor which was used in this study can provide real-time exposure, and this could give more accurate exposure data of the population especially those subpopulations that are highly exposed than fixed station monitoring