arXiv:2603.12050cs.CL2026-03被引 1

翻译风格差异源于翻译任务本身的认知负担。

Translationese as a Rational Response to Translation Task Difficulty

  • 用信息论指标衡量翻译难度,预测翻译风格差异。
  • 跨语言迁移难度比源文本复杂度影响更大。
  • 适合研究翻译认知机制或机器翻译优化者。

翻译文本与目标语原生文本存在系统性差异,即翻译腔(translationese)。现有研究多归因于语言干扰、简化或文化因素,但缺乏统一解释。本文提出翻译腔是翻译任务固有认知负荷的体现,并验证其能否由可量化的翻译任务难度预测。翻译腔以自动分类器生成的段落级翻译度得分为指标;任务难度包含源文本复杂度与跨语言迁移两部分,主要采用基于大模型意外度(LLM surprisal)的信息论指标,辅以传统句法与语义特征。使用涵盖书面与口语的英德双向语料库进行实验。结果表明,翻译腔在一定程度上可由任务难度解释,尤其在英译德中表现明显。多数情况下,跨语言迁移难度贡献大于源文本复杂度。信息论指标在书面模式下表现不劣于甚至优于传统特征,但在口语模式下无优势。源文本句法复杂度与翻译解空间熵是跨语言对与模式下的最强预测因子。

原文摘要 · Abstract (English)

Translations systematically diverge from texts originally produced in the target language, a phenomenon widely referred to as translationese. Translationese has been attributed to production tendencies (e.g. interference, simplification), socio-cultural variables, and language-pair effects, yet a unified explanatory account is still lacking. We propose that translationese reflects cognitive load inherent in the translation task itself. We test whether observable translationese can be predicted from quantifiable measures of translation task difficulty. Translationese is operationalised as a segment-level translatedness score produced by an automatic classifier. Translation task difficulty is conceptualised as comprising source-text and cross-lingual transfer components, operationalised mainly through information-theoretic metrics based on LLM surprisal, complemented by established syntactic and semantic alternatives. We use a bidirectional English-German corpus comprising written and spoken subcorpora. Results indicate that translationese can be partly explained by translation task difficulty, especially in English-to-German. For most experiments, cross-lingual transfer difficulty contributes more than source-text complexity. Information-theoretic indicators match or outperform traditional features in written mode, but offer no advantage in spoken mode. Source-text syntactic complexity and translation-solution entropy emerged as the strongest predictors of translationese across language pairs and modes.

翻译腔认知负荷信息论机器翻译

Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。