The role of noise in information-theoretic models of sentence comprehension and production

人类语言的产生和理解充满了错误：人们会犯语音错误，打字/发短信时会犯打字错误，而且经常会有背景噪音，使人无法准确地感知单词。考虑到人类语言在实践中的嘈杂性质，人们能够如此好地相互理解是令人惊讶的。人们如何在有噪音的情况下进行交流的问题尚未得到解决，这是我们工作的重点。理解人类如何理解嘈杂的语言是至关重要的，原因有两个。首先，语言技术必须能够处理嘈杂的语言输入：翻译服务需要考虑正在翻译的文本中的错误；搜索引擎需要处理噪音产生的网络内容。有关人类如何在噪音中理解语言的证据可以改进语言技术的设计。此外，在对话系统能够产生连贯的语言反应之前--可能需要几十年的时间--这类系统的任何实际应用都必须在设计时理解人类如何处理嘈杂或令人困惑的语言输入。其次，在临床方面，了解人类如何理解可能包含错误的语言将为语言理解障碍提供洞察力。最近的研究表明，失语症患者似乎比健康参与者认为输入中存在更多的错误，因此在解释语言时更依赖于他们对世界的先前信念。这项工作的应用可能会为这类患者带来更有效的诊断和治疗选择。拟议的研究有两个目标。首先，研究人员将调查语言理解过程中的噪音，其中噪音分为三类：(A)删除，使听者/读者可能遗漏原意；(B)插入，使制作者可能无意中插入什么；以及(C)互换，使制作者可能意外地交换流中的元素。其次，研究人员将研究句子产生中记忆的信息论方法，在这种方法中，记忆是语言使用中潜在错误的来源。最近的人类视觉研究表明，记忆能力最好被建模为对表示的复杂性的限制，就信息理论单位而言，称为“比特”。简单的表示只需要很少的信息，而复杂的表示需要很多信息。这项拟议中的研究将这一想法扩展到了语言上，这样，高频的单词和短语，如“男孩看到女孩”，应该很容易存储在记忆中，而频率较低的成分，如“男人遇到的女人很高”，应该很难存储在记忆中。

Human language as it is produced and understood is full of errors: people make speech errors, they make typographical errors when typing / texting, and there is often background noise that makes it impossible to perceive words accurately. Given the noisy nature of human language in practice, it is surprising that people can understand one another so well. The question of how people can communicate given noise is not yet solved, and is the focus of our work. Understanding how humans can understand noisy language is critical for two reasons. First, language technologies must be capable of processing noisy language input: translation services need to account for errors in the text being translated; search engines need to process noisily-generated web content. Evidence concerning how humans understand language in noise can lead to improvements in the design of language technologies. In addition, until dialogue systems can produce coherent language responses--likely decades away--any practical application of such systems must be designed with an understanding of how humans deal with noisy or confusing language input. Second, on the clinical side, understanding how humans understand language which might contain errors will provide insights into language comprehension disorders. Recent research has shown that individuals with aphasia appear to assume the presence of more errors in the input than healthy participants, and thus show stronger reliance on their prior beliefs about the world when interpreting language. Applications of this work may lead to more efficient diagnosis and treatment options for such patients.The goals of the proposed research are two-fold. First, the researchers will investigate noise in the process of language comprehension, where noise falls into three categories (a) deletions, such that the listener / reader might miss something that was intended; (b) insertions, such that the producer might accidentally insert something; and (c) swaps, such that the producer might accidentally switch elements in the stream. Second, the researchers will investigate an information-theoretic approach to memory in sentence production, where memory is a source of potential errors in language use. Recent human vision research suggests that memory capacity is best modeled as a limitation on the complexity of the representations, in terms of information-theoretic units called "bits". Simple representations require very few bits of information, but complex representations require many. The proposed research extends this idea to language, such that high-frequency words and phrases such as "the boy sees the girl" should be stored easily in memory, while less frequent components such as "the woman who the man met was tall" should be difficult to store in memory.