Relative Positional Encoding for Speech Recognition and Direct Translation

Transformer models are powerful sequence-to-sequence architectures that are capable of directly mapping speech inputs to transcriptions or translations. However, the mechanism for modeling positions in this model was tailored for text modeling, and thus is less ideal for acoustic inputs. In this work, we adapt the relative position encoding scheme to the Speech Transformer, where the key addition is relative distance between input states in the self-attention network. As a result, the network can better adapt to the variable distributions present in speech data. Our experiments show that our resulting model achieves the best recognition result on the Switchboard benchmark in the non-augmentation condition, and the best published result in the MuST-C speech translation benchmark. We also show that this model is able to better utilize synthetic data than the Transformer, and adapts better to variable sentence segmentation quality for speech translation.Comment: Submitted to Interspeech 202

Determining the impacts of hospital cost-sharing on the uninsured near-poor households in Vietnam

Objectives: The study objective was to identify the size of different hospital financing sources for different hospital services and their impact on the uninsured. Methods: A panel dataset of 84 public general hospitals (2005–2008) with cross-section data on hospital activity and hospital revenue was created and used to calculate unit costs of different hospital services by applying multiple regression models. The resulting risk of catastrophic health expenditure (CHE) was estimated based on official income statistics. Results: Average user fees (UF) for outpatient visits and inpatient bed days were US$4.13 and US$20.27, while actual full costs (AFC) were US$8.41 and US$36.66, respectively. These unit costs were 2.5 times higher in hospitals at the central versus the provincial level. UF for surgical inpatient bed days were 3.6 times that of non-surgical treatments (US$47.50 vs. 12.87) and AFC 5.0 times (US$101.72 vs. 20.08). UF accounted for 44.6%-77.9% of the AFC, the rest (22.1%-55.4%) was provided by direct government support (DGS). One surgical inpatient treatment at either central or provincial hospital level and one non-surgical inpatient treatment at central hospital level, immediately pushed uninsured near-poor households at risk of CHE. Conclusions: Around 45% of hospital AFC was paid by DGS, the larger rest by UF. UF have become a great financial burden on the uninsured near-poor households, who have to pay for these out-of-pocket and therefore may not utilize even necessary services. If the rate of DGS were reduced, this would have the effect of increasing UF, but the savings to Government could be spent on subsidizing insurance to ensure that a larger part of the population can cover UF through insurance, especially the near-poor households

Level of Factors impact on the Buyers’ Intention in Buying Private Health Insurance with the Case of Vietnam Non-Life Insurance Companies

The study aims to determine the influence of factors affecting the intention to purchase private health insurance at non-life insurance companies in Vietnam. The samples were surveyed from 500 people from many areas but mostly in Hanoi. The study identified and clarified 5 independent factors affecting the intention to buy private health insurance at non-life health insurance companies in Vietnam. The analysis results show 5 variables: "Past experience", "Perception of service quality of insurance companies", "Perceived behavioral control", "Attitude towards risks and private health insurance ", and the variable "Subjective norms on private health insurance" affect people's intention to buy private health insurance. Several policies have been proposed to increase customers' intention to buy private health insurance at non-life insurance companies from the analysis. To raise customer's intention to purchase private health insurance, the research team recommends non-life insurance company to improve service quality, especially after-sales service, the quality and expertise of staff, and the government to complete policies and legal framework on private health insurance. Moreover, the research team also recommend to renovate the quality of organizing the private health insurance regime and form the basis of the entire population pathology record. Keywords: private health insurance, intention to purchase, non-life insurance company. DOI: 10.7176/EJBM/12-27-06 Publication date:September 30th 202

RMDM: A Multilabel Fakenews Dataset for Vietnamese Evidence Verification

In this study, we present a novel and challenging multilabel Vietnamese dataset (RMDM) designed to assess the performance of large language models (LLMs), in verifying electronic information related to legal contexts, focusing on fake news as potential input for electronic evidence. The RMDM dataset comprises four labels: real, mis, dis, and mal, representing real information, misinformation, disinformation, and mal-information, respectively. By including these diverse labels, RMDM captures the complexities of differing fake news categories and offers insights into the abilities of different language models to handle various types of information that could be part of electronic evidence. The dataset consists of a total of 1,556 samples, with 389 samples for each label. Preliminary tests on the dataset using GPT-based and BERT-based models reveal variations in the models' performance across different labels, indicating that the dataset effectively challenges the ability of various language models to verify the authenticity of such information. Our findings suggest that verifying electronic information related to legal contexts, including fake news, remains a difficult problem for language models, warranting further attention from the research community to advance toward more reliable AI models for potential legal applications.Comment: ISAILD@KSE 202

KIT’s IWSLT 2020 SLT Translation System

This paper describes KIT’s submissions to the IWSLT2020 Speech Translation evaluation campaign. We first participate in the simultaneous translation task, in which our simultaneous models are Transformer based and can be efficiently trained to obtain low latency with minimized compromise in quality. On the offline speech translation task, we applied our new Speech Transformer architecture to end-to-end speech translation. The obtained model can provide translation quality which is competitive to a complicated cascade. The latter still has the upper hand, thanks to the ability to transparently access to the transcription, and resegment the inputs to avoid fragmentation

KIT’s IWSLT 2021 Offline Speech Translation System

This paper describes KIT’submission to the IWSLT 2021 Offline Speech Translation Task. We describe a system in both cascaded condition and end-to-end condition. In the cascaded condition, we investigated different end-to-end architectures for the speech recognition module. For the text segmentation module, we trained a small transformer-based model on high-quality monolingual data. For the translation module, our last year’s neural machine translation model was reused. In the end-to-end condition, we improved our Speech Relative Transformer architecture to reach or even surpass the result of the cascade system

GENETIC POLYMORPHISM OF 23 Y-CHROMOSOME SHORT TANDEM REPEAT LOCI IN THE KINH POPULATION OF VIETNAM

Y-chromosome microsatellites or short tandem repeats (STRs) have been proved to be ideal markers to delineate the differences between individuals in human population. Nowadays, Y-STR testing using the PowerPlex® Y23 amplification kit is considered as an extremely sensitive analysis method and has the potential to be used to perform forensic caseworks, and to explore the complexity in population substructures. However, little is known about the forensic Y-chromosome databases in the Vietnam population. In this study, 23 Y-STR loci (DYS576, DYS389I, DYS389 II, DYS448, DYS19, DYS391, DYS481, DYS549, DYS533, DYS438, DYS437, DYS570, DYS635, DYS390, DYS439, DYS392, DYS393, DYS458 DYS456, DYS643, YGATAH4, and DYS385a/b) were investigated in 120 non-related males of the Kinh population in Northern Vietnam using PowerPlex® Y23 system kit (Promega). Our results showed that allele frequencies of 23 loci in the sample population, with the calculated average gene diversity (GD) for each locus, ranged from 0.24 (DYS438) to 0.92 (DYS385a/b). In addition, a total of 120 different haplotypes were found, all of them were unique. Therefore, we found that the haplotype diversity was 1 with a discrimination capacity of 100%, which serves as an essential prerequisite for using Y-chromosomal STR with PowerPlex® Y23 System kit in forensic application in Vietnam. We also compared genetic distances between Kinh population and 10 other neighboring populations from Y-chromosome haplotype reference database (YHRD). The Kinh population is significantly different from other populations. In conclusion, it was indicated that the 23 Y-STR loci were highly genetically polymorphic in the Kinh population in Vietnam and might be of great value in forensic application