New insights into the speaker’s lexicon: Computational modelling and experimental data

对演讲者词典的新见解：计算模型和实验数据

• 批准号: 458716577
• 负责人: Professorin Dr. Audrey Bürki, Ph.D.
• 金额: --
• 依托单位: Department für Linguistik
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/458716577?language=en
• 关键词: New; insights; into; speaker; lexicon

The frequency with which we experience events shapes our subsequent processing of similar events. Language is no exception. In the study of language production, one of the first experimental effects to be discovered was the lexical frequency effect. More frequent words can be accessed and encoded more quickly. This empirical effect has shaped our understanding of the mental lexicon - how information about words is organized in memory- and of the processes involved in accessing these representations. It has been taken as evidence that words are represented in long-term memory together with information about their frequency of use. Just like some words are more frequent than others, some word sequences or utterances are more frequent than others. We say I’ll take a glass more often than I’ll take a plate and a great trip more often than a great plane. Does the frequency of the chunk impact the preparation (i.e., encoding) of this chunk? Current psycholinguistic models of language production predict that this should not be the case. In these models phrases are built on the fly. Once a given utterance has been produced, it does not leave any trace in the system. Yet recent studies have shown that similar effects arise for multi-word utterances. The phrases that speakers use more often can be encoded more quickly. This empirical result demonstrates that the language production system keeps track not only of its encounters with individual words, but also of how often these words are combined into phrases. This result requires that psycholinguistic models of language production be refined or that some of their fundamental assumptions be revisited. The present project capitalizes on this discovery. Its aim is to implement and test a novel model of language production that can account for these effects. This model views the lexicon as a network of interconnected lexical representations that evolves dynamically as a results of the speaker’s use of the network. Tools of Artificial Intelligence (i.e., linear modeling, naïve discrimination learning) will be used to simulate different versions of that model as well as an alternative model in which the system stores representations for whole phrases. Psycholinguistic experiments will be conduct to measure changes in the participants’ performance as a function of their use of the language. The outcome of these experiments will be compared to the predictions of the computational models. This project is expected to mark a turning point in the study of language production processes. It will shed a new light on the cognitive architecture of the language production system and open up new perspectives in the study of that system.

我们经历事件的频率塑造了我们对类似事件的后续处理。语言也不例外。在语言产生的研究中，最早被发现的实验效应之一是词频效应。可以更快地访问和编码更频繁的单词。这种经验效应塑造了我们对心理词汇的理解--词汇信息在记忆中是如何组织的--以及访问这些表征所涉及的过程。它已被视为证据，在长期记忆中表示的话，连同有关其使用频率的信息。就像某些单词比其他单词更频繁一样，某些单词序列或话语比其他单词更频繁。我们说我会拿一个玻璃杯比我会拿一个盘子更频繁，一次伟大的旅行比一架伟大的飞机更频繁。组块的频率是否影响准备（即，编码）的这个块？目前的心理语言学语言产生模型预测，这不应该是这样的。在这些模型中，短语是在飞行中建立的。一旦一个给定的话语已经产生，它不会在系统中留下任何痕迹。然而，最近的研究表明，类似的效果出现在多词话语中。说话者更经常使用的短语可以更快地编码。这一实验结果表明，语言产生系统不仅记录了它与单个单词的相遇，而且还记录了这些单词组合成短语的频率。这一结果要求语言产生的心理语言学模型得到完善，或者重新审视他们的一些基本假设。本项目利用了这一发现。其目的是实施和测试一种新的语言产生模型，可以解释这些影响。该模型将词汇看作是一个相互连接的词汇表征网络，随着说话者对网络的使用而动态演变。人工智能工具（即，线性建模、朴素判别学习）将用于模拟该模型的不同版本以及系统存储整个短语的表示的替代模型。将进行心理语言学实验，以衡量参与者的表现变化，作为他们使用语言的功能。这些实验的结果将与计算模型的预测进行比较。该项目有望成为语言产生过程研究的一个转折点。它将为语言产生系统的认知结构提供新的视角，并为语言产生系统的研究开辟新的途径。