VLSP workshop

This paper presents the first challenge on recognizing textual entailment (RTE), also known as natural language inference (NLI), held in a Vietnamese Language and Speech Processing workshop (VLSP 2021). The challenge aims to determine, for a given pair of sentences, whether the two sentences semantically agree, disagree, or are neutral/irrelevant to each other.

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Based on the motivation behind these achievements, this paper describes our approach based on fine-tuning pretrained multilingual language models (XLM-R, InfoXLM) to tackle the shared task “Vietnamese and English Vietnamese Textual Entailment” at the 8th International Workshop on Vietnamese Language and Speech Processing (VLSP 20211).

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The VLSP 2021 is the eighth annual international workshop whose campaign was organized at the University of Information Technology, Vietnam National University, Ho Chi Minh City (UIT-VNU-HCM). This was the first time we organized the Speaker Verification shared task with two subtasks SV-T1 and SV-T2. SV-T1 focuses on the development of SV models with limited data, and SV-T2 focuses on testing the capability and the robustness of SV systems.

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This paper presents VieCap4H, a grand data challenge on automatic image caption generation for the healthcare domain in Vietnamese. VieCap4H is held as part of the eighth annual workshop on Vietnamese Language and Speech Processing (VLSP 2021).

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This paper presents a Vietnamese automatic speech recognition challenge for the eighth annual workshop on Vietnamese Language and Speech Processing (VLSP 2021). There are two sub-tasks in the challenge.

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Text-To-Speech (TTS) was one of nine shared tasks in the eighth annual international VLSP 2021 workshop. All three previous TTS shared tasks were conducted on reading datasets. However, the synthetic voices were not natural enough for spoken dialog systems where the computer must talk to the human in a conversation.

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Sentiment analysis is a Natural Language Processing (NLP) task of identifying or extracting the sentiment content of a text unit. This task has become an active research topic since the early 2000s. This paper describes the built datasets as well as the evaluation results of the systems participating to these campaigns.

16p viconandoyle2711 29-08-2019 24 0   Download

Named Entities (NE) are phrases that contain the names of persons, organizations, locations, times and quantities, monetary values, percentages, etc. In this paper, we describe the datasets as well as the evaluation results obtained from these two campaigns.

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