Text simplification (TS) is the process of generating easy-to-understand sentences from a given sentence or piece of text. The aim of TS is to reduce both the lexical (which refers to vocabulary complexity and meaning) and syntactic (which refers to the sentence structure) complexity of a given text or sentence without the loss of meaning or nuance. In this paper, we present \textsc{SimpLex}, a novel simplification architecture for generating simplified English sentences. To generate a simplified sentence, the proposed architecture uses either word embeddings (i.e., Word2Vec) and perplexity, or sentence transformers (i.e., BERT, RoBERTa, and GPT2) and cosine similarity. The solution is incorporated into a user-friendly and simple-to-use software. We evaluate our system using two metrics, i.e., SARI, and Perplexity Decrease. Experimentally, we observe that the transformer models outperform the other models in terms of the SARI score. However, in terms of Perplexity, the Word-Embeddings-based models achieve the biggest decrease. Thus, the main contributions of this paper are: (1) We propose a new Word Embedding and Transformer based algorithm for text simplification; (2) We design \textsc{SimpLex} -- a modular novel text simplification system -- that can provide a baseline for further research; and (3) We perform an in-depth analysis of our solution and compare our results with two state-of-the-art models, i.e., LightLS [19] and NTS-w2v [44]. We also make the code publicly available online.

翻译：文本简化（TS）是指从给定句子或文本片段生成易于理解句子的过程。其目标是在不损失语义或细微含义的前提下，降低给定文本或句子的词汇复杂性（涉及词汇复杂度与含义）与句法复杂性（涉及句子结构）。本文提出了一种新颖的简化架构 \textsc{SimpLex}，用于生成简化的英语句子。该架构通过以下两种方式生成简化句子：使用词嵌入（如Word2Vec）与困惑度，或使用句子变换器（如BERT、RoBERTa和GPT2）与余弦相似度。该解决方案被集成到一款用户友好且易于使用的软件中。我们使用SARI和困惑度下降两个指标对系统进行评估。实验发现，在SARI得分方面，变换器模型优于其他模型；但在困惑度方面，基于词嵌入的模型实现了最大降幅。因此，本文的主要贡献包括：（1）提出了一种基于词嵌入与变换器的文本简化新算法；（2）设计了模块化的新型文本简化系统 \textsc{SimpLex}，可为后续研究提供基线；（3）对解决方案进行了深入分析，并将结果与两个最先进的模型（LightLS [19] 和 NTS-w2v [44]）进行了对比。此外，我们已在线公开了相关代码。