在 11 种语言中测试惊奇理论的预测结果

IF 4.2 1区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Transactions of the Association for Computational Linguistics Pub Date : 2023-07-07 DOI:10.1162/tacl_a_00612
Ethan Gotlieb Wilcox, Tiago Pimentel, Clara Meister, Ryan Cotterell, R. Levy
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引用次数: 0

摘要

摘要 惊奇理论(surprisal theory)认为,可预测性较低的单词应该需要更多的时间来处理,单词的可预测性量化为惊奇(surprisal),即上下文中的负对数概率。虽然支持惊奇理论预测的证据已被广泛复制,但其中大部分都集中在非常狭窄的数据片段上:以英语为母语的人阅读英语文本。事实上,目前还没有全面的多语言分析。我们通过研究五大语系 11 种不同语言中惊奇和阅读时间之间的关系,填补了目前文献中的这一空白。根据在单语和多语语料库中训练的语言模型得出的估计值,我们检验了与惊奇理论相关的三个预测:(i) 惊奇是否能预测阅读时间;(ii) 预期惊奇(即上下文熵)是否能预测阅读时间;(iii) 惊奇与阅读时间之间的关联函数是否是线性的。我们发现这三个预测在跨语言研究中都得到了证实。通过关注更多样化的语言,我们认为这些结果提供了迄今为止信息理论与跨语言增量语言处理之间最稳健的联系。
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Testing the Predictions of Surprisal Theory in 11 Languages
Abstract Surprisal theory posits that less-predictable words should take more time to process, with word predictability quantified as surprisal, i.e., negative log probability in context. While evidence supporting the predictions of surprisal theory has been replicated widely, much of it has focused on a very narrow slice of data: native English speakers reading English texts. Indeed, no comprehensive multilingual analysis exists. We address this gap in the current literature by investigating the relationship between surprisal and reading times in eleven different languages, distributed across five language families. Deriving estimates from language models trained on monolingual and multilingual corpora, we test three predictions associated with surprisal theory: (i) whether surprisal is predictive of reading times, (ii) whether expected surprisal, i.e., contextual entropy, is predictive of reading times, and (iii) whether the linking function between surprisal and reading times is linear. We find that all three predictions are borne out crosslinguistically. By focusing on a more diverse set of languages, we argue that these results offer the most robust link to date between information theory and incremental language processing across languages.
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来源期刊
CiteScore
32.60
自引率
4.60%
发文量
58
审稿时长
8 weeks
期刊介绍: The highly regarded quarterly journal Computational Linguistics has a companion journal called Transactions of the Association for Computational Linguistics. This open access journal publishes articles in all areas of natural language processing and is an important resource for academic and industry computational linguists, natural language processing experts, artificial intelligence and machine learning investigators, cognitive scientists, speech specialists, as well as linguists and philosophers. The journal disseminates work of vital relevance to these professionals on an annual basis.
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