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These are organized into a tree structure, shown schematically in 1.2.
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.We can also construct special tabulations (known as paradigms) to illustrate contrasts and systematic variation, as shown in 1.3 for three verbs. At the most abstract level, a text is a representation of a real or fictional speech event, and the time-course of that event carries over into the text itself.A text could be a small unit, such as a word or sentence, or a complete narrative or dialogue.Finally, notice that even though TIMIT is a speech corpus, its transcriptions and associated data are just text, and can be processed using programs just like any other text corpus.
Therefore, many of the computational methods described in this book are applicable.
Despite its complexity, the TIMIT corpus only contains two fundamental data types, namely lexicons and texts.
As we saw in 2., most lexical resources can be represented using a record structure, i.e. A lexical resource could be a conventional dictionary or comparative wordlist, as illustrated.
: Structure of the Published TIMIT Corpus: The CD-ROM contains doc, train, and test directories at the top level; the train and test directories both have 8 sub-directories, one per dialect region; each of these contains further subdirectories, one per speaker; the contents of the directory for female speaker A fourth feature of TIMIT is the hierarchical structure of the corpus.
With 4 files per sentence, and 10 sentences for each of 500 speakers, there are 20,000 files.
Two sentences, read by all speakers, were designed to bring out dialect variation: The remaining sentences were chosen to be phonetically rich, involving all phones (sounds) and a comprehensive range of diphones (phone bigrams).