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Finally, TIMIT includes demographic data about the speakers, permitting fine-grained study of vocal, social, and gender characteristics.TIMIT illustrates several key features of corpus design.First, the corpus contains two layers of annotation, at the phonetic and orthographic levels.In general, a text or speech corpus may be annotated at many different linguistic levels, including morphological, syntactic, and discourse levels.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.Moreover, notice that all of the data types included in the TIMIT corpus fall into the two basic categories of lexicon and text, which we will discuss below.

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A thesaurus also consists of record-structured data, where we look up entries via non-key fields that correspond to topics.These are organized into a tree structure, shown schematically in 1.2.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.TIMIT was developed by a consortium including Texas Instruments and MIT, from which it derives its name.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.

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