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Based on specificity and sensitivity, the first choice for the most appropriate screening tool for use in Vietnam is the NRS-2002, following by the MST + BMI, MUST, and BMI alone at the cut-off value of 21 kg/m. Further investigation on the feasibility and acceptability are required to determine the most appropriate screening tools for use within the Vietnamese context.

Aim Low‐dietary intake is a common problem and cause of malnutrition during hospitalisation. This study aims to determine the current dietary intake and food sources of hospitalised adults in Ho Chi Minh City. Methods Participants were adult patients from six general public hospitals in a multi‐site survey undertaken in 2016. Dietary intakes for all foods consumed in the previous day were collected via interview using the 24 hours recall method. Nutritional status was assessed using Subjective Global Assessment or BMI. Results Data were collected from 887 participants. Most food consumed in hospital was from non‐regulated foodservices. Food was self‐provided and home‐cooked (27.7%), bought from outside the hospital (13.6%), from the hospital canteen (16.8%) or a combination of these (39.4%). Only 1.3% of food was provided by the hospital. Energy intakes were very low with a median of 3550 kJ/day; and only 4.2% of participants met 100% of their energy requirements. Decreased appetite, fullness or restrictions due to medical indications were the most common reasons for low‐dietary intake. Malnourished participants were 2.2 times more likely to have low‐dietary intake compared to well‐nourished participants. Conclusions Non‐regulated foodservices in hospital were not able to meet the dietary requirements of patients leading to hospital malnutrition. Standardisation of food from on‐site canteens, covering meal costs from universal medical insurance, and developing guides for food provisioning for patients’ families are potential solutions to improve patient nutritional status.

International audienceThis paper presents our first attempt at constructing a Vietnamese-French statistical machine translation system. Since Vietnam-ese is an under-resourced language, we concentrate on building a large Vietnamese-French parallel corpus. A document alignment method based on publication date, special words and sentence alignment result is proposed. The paper also presents an application of the obtained parallel corpus to the construction of a Vietnamese-French statistical machine translation system, where the use of different units for Vietnamese (syllables , words, or their combinations) is discussed

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The paper introduces a method for automatic translation of Vietnamese text into Muong speech in two dialects, Muong Bi - Hoa Binh and Muong Tan Son - Phu Tho, which are all unwritten dialects of the Muong language. Due to the very close relationship between the Vietnamese and Muong languages, the translation system was built to look like a cross-lingual speech synthesis system, in which the input is the text of one language (i.e., the Vietnamese) and the output is the speech of another language (i.e., the two Muong dialects). The system used the modern sequence-to-sequence TTS neural models Tacotron2 and WaveGlow. The evaluation results showed a high quality of translation (with a fluency score of 4.61/5.0 and an adequacy score of 4.79/5.0) and also synthesized speech quality (with naturalness on the MOS scale of 4.68/5.0 and intelligibility of 94.60%). The received results show that the applicability of the proposed system to other minority languages is promising, especially in the case of unwritten languages.