Lexical normalization, a fundamental task in Natural Language Processing (NLP), involves the transformation of words into their canonical forms. This process has been proven to benefit various downstream NLP tasks greatly. In this work, we introduce Vietnamese Lexical Normalization (ViLexNorm), the first-ever corpus developed for the Vietnamese lexical normalization task. The corpus comprises over 10,000 pairs of sentences meticulously annotated by human annotators, sourced from public comments on Vietnam's most popular social media platforms. Various methods were used to evaluate our corpus, and the best-performing system achieved a result of 57.74% using the Error Reduction Rate (ERR) metric (van der Goot, 2019a) with the Leave-As-Is (LAI) baseline. For extrinsic evaluation, employing the model trained on ViLexNorm demonstrates the positive impact of the Vietnamese lexical normalization task on other NLP tasks. Our corpus is publicly available exclusively for research purposes.

翻译：词汇规范化是自然语言处理（NLP）中的一项基础任务，旨在将词汇转换为其规范形式。已有研究表明，该过程能为多种下游NLP任务带来显著效益。本文提出越南语词汇规范化（ViLexNorm）语料库——首个专为越南语词汇规范化任务开发的语料库。该语料库包含超过10,000对人工精标注的句子，数据来源于越南最流行的社交媒体平台上的公开评论。我们采用多种方法对该语料库进行评估，其中最佳系统在留原词（LAI）基线基础上，使用错误减少率（ERR）指标（van der Goot, 2019a）达到了57.74%的结果。在外在评估中，采用ViLexNorm训练的模型证明了越南语词汇规范化任务对其他NLP任务的积极影响。本语料库仅限研究用途公开使用。