Doctoral Dissertation Research: The acquisition of phoneme categories

对于孩子来说，学习语言毫不费力，只有学习第二语言的成年人才能瞥见学习语言所涉及的众多复杂性。它们的范围从单词与意义的关联，到像语音分类这样看似简单的事情。为了最好地说明这一点，我们可以看两个例子：英语和印地语使用者之间的感知差异，以及英语和日语使用者之间的感知差异。说英语的人很难分辨出“pear”中的“p”和“spare”中的“p”的区别，尽管实际上它们的发音完全不同。另一方面，说印地语的人听出这种区别是没有问题的。再举一个例子，说英语的人可以很容易地告诉你“light”和“right”的开头是两个不同的音，但说日语的人却很难分辨出这两个词之间的区别。所有这些困难都是人类婴儿在第一次学习语言时非常有效的学习机制的副产品。甚至在我们做出有意识的决定之前，人类的大脑就会无意识地、自动地将我们不断接收到的大量信息整理成有序的数据。这项研究关注的是确定印地语婴儿接收到哪些关键信息，从而导致他或她（无意识地）确定这是两个不同的“p”音，而英语婴儿确定它们是相同的音；或者什么信息导致日本婴儿在习得日语时忽略了“l”和“r”的区别，而没有导致英国婴儿忽略同样的区别。这项研究通过解决人类如何学习类别，为认知科学领域的广泛理论问题做出了贡献，同时也带来了实际应用，如更有效的第二语言学习技术和语言病理学的进步。先前的研究已经确定了人类在对声音进行分类时使用的至少两个主要线索：学习者不断增长的词汇量（“词汇线索”）和语音流中的声学特性（“声学线索”）。词汇提示将出现在相似单词环境中的声音（“light”和“right”）组合成一个声音类别。声学线索将声音映射到一些声学地图上，并在这张地图上挑选出高频区域。这项研究利用过去的观察，成年人可以无意识地模拟，至少在某种程度上，婴儿的学习经验方面的实验室设置。这个实验将通过向参与者展示一种人工语言来测试成年人对这两种线索的依赖程度，在这种语言中，词汇线索和声音线索给参与者提供了相互矛盾的信息。通过这种方式，这项研究将有助于更好地理解人类大脑在对语音进行分类时做出的无意识决定。这项研究解决了语言学和认知科学中的两个基本问题：(1)人类大脑如何形成复杂的类别；(2)有多少语言是通过专门的语言特定模块获得的，有多少语言可以归因于一般的认知机制。

Language comes effortlessly to children, and only adults learning a second language get a glimpse of the numerous intricacies involved in learning a language. These range from correlation of word to meaning, to something as deceptively simple as the categorization of speech sounds. To best illustrate this, we can look at two examples: differences in perception between English and Hindi speakers, and differences in perception between English and Japanese speakers. English speakers have trouble hearing the difference between the "p" in "pear" and the "p" in "spare," even though they are in reality pronounced quite differently. A speaker of Hindi on the other hand would have no trouble hearing this difference. To take another example, while English speakers could easily tell you that "light" and "right" begin with two different sounds, Japanese speakers find it very difficult to hear the difference between these two words. All of these difficulties arise as a byproduct of the human infant's very efficient learning mechanism when (s)he is first learning a language. The human brain unconsciously and automatically sorts the large amount of information we are constantly receiving into ordered data, even before we make conscious decisions. This study is concerned with determining what critical pieces of information were received by the Hindi infant to lead him or her to (unconsciously) determine that those were two different "p" sounds, while the English infant determined that they were the same sound; or what information led the Japanese infant to ignore the difference between "l" and "r" when acquiring Japanese, but did not lead the English infant to ignore the same difference. This study both contributes to broad theoretical issues within cognitive science by addressing how categories are learned by humans, and also leads to practical applications, such as more efficient second language learning techniques and advancements in speech pathology.Previous work has identified at least two main cues that humans use when categorizing sounds: the learner's growing vocabulary ("vocabulary cue") and acoustic properties found within a stream of speech ("acoustic cue"). The vocabulary cue groups together sounds occurring in similar word environments ("light" and "right") into a single sound category. The acoustic cue maps sounds into some acoustic map and picks out regions of high frequencies on this map. This study makes use of past observations that adults can unconsciously simulate, at least to some degree, aspects of the infant's learning experience within a laboratory setting. This experiment will test how much adults rely on each of these two cues by presenting participants with an artificial language where the vocabulary cue and the acoustic cue give the participant conflicting information. In this way, the research will contribute to a better understanding of what unconscious decisions the human brain makes when categorizing speech sounds. This study addresses two fundamental issues within linguistics and within cognitive science: (1) how the human brain forms complex categories, and (2) how much of language is acquired through specialized language-specific modules and how much of language can be attributed to general cognitive mechanisms.