Discourse markers are words and expressions (such as: firstly, then, for example, because, as a result, likewise, in comparison, in contrast) that explicitly state the relational structure of the information in the text, i.e. signalling a sequential relationship between the current message and the previous discourse. Using these markers improves the cohesion and coherence of texts, facilitating reading comprehension. Although often included in tools that support the rhetoric structuring of texts, discourse markers have hardly been explored in writing support tools for learners of a second language. However, learners of a second language, including those at advanced levels, have trouble producing these lexical items, frequently replacing them with items from their native language or with literal translations of items in their own language, which often do not result in proper lexical items in the second language. In addition, students learn a single marker per function and use it repeatedly, producing monotonous texts. With the aim of contributing to reducing these difficulties, this paper presents a lexicon that will be used to support the task of automatically detecting and correcting discourse marker errors. Several heuristics have been evaluated to generate different types of errors. Automatic translation methods were used to semi-automatically compile the lexicon used in these heuristics. Similarity measures were also combined with these heuristics to correct discourse marker errors. The evaluated methods proved to be suitable for the task of identifying some types of discourse marker errors and can potentially identify many others, as long as new lexical inputs are incorporated into them.

中文翻译：

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西班牙裔母语人士在葡萄牙语学术著作中自动检测和纠正话语标记错误

话语标记是单词和表达方式（例如：首先是，然后例如是因为，作为结果，同样是作为对比，相反），它们明确说明了文本中信息的关系结构，即表示之间的顺序关系当前信息和先前的论述。使用这些标记可以提高文本的凝聚力和连贯性，从而有助于阅读理解。尽管通常包含在支持文本的修辞结构的工具中，但在为第二语言的学习者编写支持工具时几乎没有探讨话语标记。但是，第二语言的学习者（包括高级语言学习者）在生成这些词汇项目时会遇到麻烦，经常用其母语中的项目或他们自己语言中项目的直译来代替它们，这通常不会导致用第二种语言显示适当的词汇。此外，学生可以为每个功能学习单个标记，然后重复使用它，从而产生单调的文本。为了有助于减少这些困难，本文提出了一个词典，该词典将用于支持自动检测和纠正话语标记错误的任务。已经评估了几种启发式方法来生成不同类型的错误。自动翻译方法用于半自动编译这些启发式方法中使用的词典。相似性度量也与这些试探法相结合以纠正话语标记错误。经评估，这些方法非常适合识别某些类型的话语标记错误，并可能识别出许多其他方法，