Titlebook: Artificial Intelligence in Data and Big Data Processing; Proceedings of ICABD Ngoc Hoang Thanh Dang,Yu-Dong Zhang,Bo-Hao Chen Conference pr

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誘騙

Vietnamese Text Summarization Based on Neural Network Modelss time and effort. This paper investigates several text summarization models based on neural networks, including extractive summarization, abstractive summarization, and abstractive summarization based on the re-writer approach and bottom-up approach. We perform experiments on the CTUNLPSum dataset

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Adapting Cross-Lingual Model to?Improve Vietnamese Dependency Parsingrt model in this task and used it as a knowledge base to solve more complex problems. However, to achieve high accuracy in a dependency parsing model, it takes significant time and labor to build a large amount of annotated treebanks. For languages with little or no annotated treebanks, some approac

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Determinanten der Familienmodellwahl,e proposed function including: (i) the overlap area; (ii) the distances; (iii) the side length. Especially, the Updated-IoU loss function is extremely concentrates on the overlap areas, and predicted object localization to obtain the higher position accuracy performance. In this way, the proposal al

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Determinanten der Familienmodellwahl,yleSpeech can synthesize a high fidelity voice with only 36 utterances (about 3?min) in training data. Furthermore, the experimental results prove that model can learn to speak in a new voice with only one small reference record (about 5?s) of the target voice without any fine-tune stage and get a c