Neurolinguistics-based Synthetic Dataset

本研究创建的Neurolinguistics-based Synthetic Dataset旨在解决Broca's Aphasia患者句子生成问题。该数据集由20,000个训练样本和10,000个测试样本组成，每个样本包含一个语法正确的句子和一个对应的合成失语症句子。数据集通过模拟失语症患者的语言特征，如句子长度、名词/动词比率和简单/复杂句子比率，来生成合成失语症句子。该数据集的应用领域是开发辅助技术，帮助失语症患者更有效地沟通。

The Neurolinguistics-based Synthetic Dataset created in this study aims to address the sentence generation challenges faced by patients with Broca's Aphasia. This dataset comprises 20,000 training samples and 10,000 test samples, with each sample containing a grammatically correct sentence and a corresponding synthetic aphasic sentence. The synthetic aphasic sentences are generated by simulating the linguistic characteristics of aphasic patients, such as sentence length, noun/verb ratio, and the ratio of simple to complex sentences. The application scenario of this dataset lies in developing assistive technologies to help aphasic patients communicate more effectively.

搜集汇总

背景与挑战

背景概述

Neurolinguistics-based Synthetic Dataset 是一个用于解决Broca's Aphasia患者句子生成问题的合成数据集，包含30,000个样本（20,000个训练和10,000个测试），每个样本由语法正确句子和模拟失语症语言特征（如句子长度和句子结构比率）的合成句子组成。该数据集旨在开发辅助技术，帮助失语症患者改善沟通效果。