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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.This last observation is less surprising when we consider that text and record structures are the primary domains for the two subfields of computer science that focus on data management, namely text retrieval and databases.A notable feature of linguistic data management is that usually brings both data types together, and that it can draw on results and techniques from both fields.

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.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.With 4 files per sentence, and 10 sentences for each of 500 speakers, there are 20,000 files.

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