Bootstrapping (linguistics)

Bootstrapping is a term used in language acquisition in the field of linguistics. It refers to the idea that humans are born innately equipped with a mental faculty that forms the basis of language. It is this language faculty that allows children to effortlessly acquire language. As a process, bootstrapping can be divided into different domains, according to whether it involves semantic bootstrapping, syntactic bootstrapping, prosodic bootstrapping, or pragmatic bootstrapping. Bootstrapping is a term used in language acquisition in the field of linguistics. It refers to the idea that humans are born innately equipped with a mental faculty that forms the basis of language. It is this language faculty that allows children to effortlessly acquire language. As a process, bootstrapping can be divided into different domains, according to whether it involves semantic bootstrapping, syntactic bootstrapping, prosodic bootstrapping, or pragmatic bootstrapping. In literal terms, a bootstrap is the small strap on a boot that is used to help pull on the entire boot. Similarly in computer science, booting refers to the startup of an operation system by means of first initiating a smaller program. Therefore, bootstrapping refers to the leveraging of a small action into a more powerful and significant operation.Bootstrapping in linguistics was first introduced by Steven Pinker as a metaphor for the idea that children are innately equipped with mental processes that help initiate language acquisition. Bootstrapping attempts to identify the language learning processes that enable children to learn about the structure of the target language. Bootstrapping has a strong link to connectionist theories which model human cognition as a system of simple, interconnected networks. In this respect, connectionist approaches view human cognition as a computational algorithm. On this view, in terms of learning, humans have statistical learning capabilities that allow them to problem solve. Proponents of statistical learning believe that it is the basis for higher level learning, and that humans use the statistical information to create a database which allows them to learn higher-order generalizations and concepts. For a child acquiring language, the challenge is to parse out discrete segments from a continuous speech stream. Research demonstrates that, when exposed to streams of nonsense speech, children use statistical learning to determine word boundaries. In every human language, there are certain sounds that are more likely to occur with each other: for example, in English, the sequence is attested (stop), but the sequence * is not. It appears that children can detect the statistical probability of certain sounds occurring with one another, and use this to parse out word boundaries. Utilizing these statistical abilities, children appear to be able to form mental representations, or neural networks, of relevant pieces of information. Pieces of relevant information include word classes, which in connectionist theory, are seen as each having an internal representation and transitional links between concepts. Neighbouring words provide concepts and links for children to bootstrap new representations on the basis of their previous knowledge. The innateness hypothesis was originally coined by Noam Chomsky as a means to explain the universality in language acquisition. All typically-developing children with adequate exposure to a language will learn to speak and comprehend the language fluently. It is also proposed that despite the supposed variation in languages, they all fall into a very restricted subset of the potential grammars that could be infinitely conceived. Chomsky argued that since all grammars universally deviate very little from the same general structure and children seamlessly acquire language, humans must have some intrinsic language learning capability that allows us to learn language. This intrinsic capability was hypothesized to be embedded in the brain, earning the title of language acquisition device (LAD). According to this hypothesis, the child is equipped with knowledge of grammatical and ungrammatical types, which they then apply to the stream of speech they hear in order to determine the grammar this stream is compatible with. The processes underlying this LAD relates to bootstrapping in that once a child has identified the subset of the grammar they are learning, they can then apply their knowledge of grammatical types in order to learn the language-specific aspects of the word. This relates to the Principles and Parameters theory of linguistics, in that languages universally consist of basic, unbroken principles and vary by specific parameters. Semantic bootstrapping is a linguistic theory of language acquisition which proposes that children can acquire the syntax of a language by first learning and recognizing semantic elements and building upon, or bootstrapping from, that knowledge. According to Pinker, semantic bootstrapping requires two critical assumptions to hold true: When discussing the acquisition of temporal contrasts, the child must first have a concept of time outside of semantics. In other words, the child must be able to have some mental grasp on the concept of events, memory, and general progression of time before attempting to conceive it semantically. Semantics, especially with regard to events and memory concepts, appears to be far more language-general, with meanings being more universal concepts rather than the individual segments being used to represent them. For this reason, semantics requires far more cognition than external stimuli in acquiring it, and relies much on the innate capability of the child to develop such abstraction; the child must first have a mental representation of the concept, before attempting to link a word to that meaning. In order to actually learn time events, several processes must occur: