A text corpus is a collection of spoken or written texts used for linguistic research. It allows for analysis of various aspects of language and is an efficient way to conduct research. Corpora are stored on computers and can be searched using software programs. Zipf’s Law helps explain the frequency of words in a language. Text corpora are useful for both human and computational linguistics, enabling advances in speech recognition technology.
A text corpus is a collection of texts, spoken or written, which forms the basis for corpus linguistic research. Memorizing these large banks of text allows researchers to analyze various aspects of any language. A text corpus is an efficient way to conduct research because, once the material is collected, it can be used to investigate a variety of language-related issues, including morphology, syntax, vocabulary, and pragmatics. Unlike older linguistic research methods, a corpus of text allows researchers to look at language based on how it is actually being used in context, rather than how it could hypothetically be used. Linguists typically have access to much larger samples of data than they did when they were limited to data they could independently collect in a limited amount of time with limited financial resources.
Corpora are usually stored on a computer, so software programs can be created to facilitate searching. A common way to use a corpus of text is to count the total number of words in the texts, then count and rank the number of times certain words have appeared. The relationship that is created between the number of total words and specific words is known as Zipf’s law. This ratio helps explain the frequency of words in a language. Understanding Zipf’s Law helps computer programmers design computer software that meets the needs of a given language. They can count and predict how often certain words and phrases will be used as input.
Another way to use a text corpus is to label specific elements in it that the researcher wants to study. An example of how this could be used is to count how many times the passive voice appears in different genres of text. Tagging has also been useful in creating computer programs that assist people in their daily lives. Partial speech labeling has been central to the development of speech recognition software. In English, for example, the same word might have more than one part of speech. Multisyllabic words are often underlined differently to signal which part of speech is being used. The noun “object” is stressed on the first syllable, but the verb “object” is stressed on the second syllable. Marking the noun form of “object” helps the computer program both read it correctly aloud and recognize it when “object” is said by a human.
Text corpora are useful for both human linguistics and computational linguistics. They allow you to conduct research that helps people better understand the language used by humans, which in turn helps to develop the language used by computers. Great strides have been made in speech recognition technology, enabling consumers to verbally control computers in their offices, homes and vehicles. Continued advances will allow humans to communicate with computers as naturally as they do with each other.
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