The same holds true of text corpora, in the sense that the original text usually has an external source, and is considered to be an immutable artifact.
Any transformations of that artifact which involve human judgment — even something as simple as tokenization — are subject to later revision, thus it is important to retain the source material in a form that is as close to the original as possible.
Structured collections of annotated linguistic data are essential in most areas of NLP, however, we still face many obstacles in using them.
The goal of this chapter is to answer the following questions: Along the way, we will study the design of existing corpora, the typical workflow for creating a corpus, and the lifecycle of corpus.
The inclusion of speaker demographics brings in many more independent variables, that may help to account for variation in the data, and which facilitate later uses of the corpus for purposes that were not envisaged when the corpus was created, such as sociolinguistics.
A third property is that there is a sharp division between the original linguistic event captured as an audio recording, and the annotations of that event.
In that case, the previous value of the field is restored, and the user has to enter the data again.
It was designed to provide data for the acquisition of acoustic-phonetic knowledge and to support the development and evaluation of automatic speech recognition systems.Let’s take a look at how to do that with a text field that is only supposed to have a value of either ‘AAAA’ or ‘BBBB’ (yes, I know that this does not make much sense in a real PDF form).So, if the user enters ‘01234’ we should see an error message that would instruct the user about what type of data is valid for this field.Like the Brown Corpus, which displays a balanced selection of text genres and sources, TIMIT includes a balanced selection of dialects, speakers, and materials.For each of eight dialect regions, 50 male and female speakers having a range of ages and educational backgrounds each read ten carefully chosen sentences.