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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.

Moreover, even at a given level there may be different labeling schemes or even disagreement amongst annotators, such that we want to represent multiple versions.

A second property of TIMIT is its balance across multiple dimensions of variation, for coverage of dialect regions and diphones.

: 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.

At the top level there is a split between training and testing sets, which gives away its intended use for developing and evaluating statistical models.

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.

It may come with annotations such as part-of-speech tags, morphological analysis, discourse structure, and so forth.

As we saw in the IOB tagging technique (7.), it is possible to represent higher-level constituents using tags on individual words.

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