Corpus can simply be defined as a collection of linguistic data both spoken or writen. However, can all linguistic data be defined as 'Corpus'? Although there are some defintions, there is a consensus among linguists that a corpus should ideally be (1) machine readable, (2) authentic, (3) representative enough to be a sample of a language variety. By fulfilling those three requirements, a collection of linguistic data can be called corpus.
Among the requirements, second and third points are quite familiar to linguists. Unlike those two, the first term 'machine readable' is more familiar to computer scientists . For this reason, this posting highlights this term. Another essential focus is preprocessing stage of a corpus.
Machine Readability
Why 'machine readable'? The term 'readable' is closely related to 'machine recognition'. Machine can refer to standalone tool such as: iPad, portable text-reader etc, but it mostly refers to computer. Computer recognition is essential for tagging, extraction and other NLP tasks. They cannot be excecuted work unless linguistic data is readable. Therefore, linguistic data that is not recognized by computer must be converted to readable format. For example, handwriting must be scanned first and later be converted to computer-recognizable format. Let's say, you turn it into pdf or word format.
There you go, you have your linguistic data. But what is meant by 'machine readable' is not only this. Your linguistic data must also be able to be 'processed' to further perform some NLP tasks such as pattern matching or extraction.
