符号学视角下翻译教学中的审美误区

Aesthetic Misconceptions in Translation Teaching from a Semiotic Perspective

摘要: 人工智能时代机器翻译已能高效完成基础语码转换，翻译教学的核心命题正从“译得正确”转向“译得美好”。文章以艾柯符号学美学为理论视角，结合刘宓庆翻译美学三维框架，系统诊断当前翻译教学中“静态单一”的审美误区，并提出“动态多元”的重构路径。研究发现，当前翻译教学的审美窄化体现为三重困境：审美客体层面，教材选篇对“美”进行筛选清洗，呈现封闭化特征，且审美类型局限于文学领域，忽略了科技、法律、广告等非文学文本的功能性审美维度；审美主体层面，学生被规训为被动的技巧执行者，审美主体性被悬置；审美再现层面，评价标准固守“忠实通顺”的静态尺度，审美再现趋于机械化。基于艾柯“开放的作品”“模范读者”与美学编码理论，本文从审美客体、主体、再现三个维度提出对应重构路径，指出在人机协作成为行业主流模式的背景下，审美判断与创造性再现能力是人类译者核心价值的重要维度——算法可完成符号转换并提供多元翻译参考，而译者则在AI辅助下于跨语言文化语境中实现独一无二的审美重建。

Abstract: In the era of artificial intelligence, machine translation has become capable of efficiently performing fundamental language conversion. The core focus of translation education has shifted from “correct translation” to “beautiful translation.” This article employs Eco’s semiotic aesthetics as a theoretical framework, combined with Liu Miqing’s three-dimensional translation aesthetics model, to systematically identify the “static and monolithic” aesthetic pitfalls in contemporary translation teaching and proposes a “dynamic and pluralistic” reconstruction approach. The study reveals that current aesthetic narrowing in translation education manifests in three challenges: at the aesthetic object level, textbook selections filter and distill notions of “beauty,” resulting in a closed-off representation, with aesthetic categories largely confined to the literary domain while neglecting the functional aesthetic dimensions of non-literary texts such as scientific, legal, and advertising materials; at the aesthetic subject level, students are trained as passive technical executors, with their aesthetic agency marginalized; at the aesthetic representation level, evaluation criteria remain rigidly tied to static standards of “faithfulness and fluency,” leading to mechanical aesthetic reproduction. Drawing on Eco’s concepts of the “open work,” “model reader,” and aesthetic coding theory, this paper proposes corresponding reconstruction pathways across three dimensions—aesthetic object, subject, and representation—and emphasizes that, against the backdrop of human-machine collaboration becoming the dominant industry model, aesthetic judgment and creative representation capabilities constitute a crucial dimension of human translators’ core value. While algorithms can handle symbolic conversion and provide diverse translation references, translators, augmented by AI, can achieve unique aesthetic reconstruction within cross-linguistic and cultural contexts.