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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.
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.
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.
The remaining three sentences read by each speaker were unique to that speaker (for coverage). You can access its documentation in the usual way, using This gives us a sense of what a speech processing system would have to do in producing or recognizing speech in this particular dialect (New England).As in other chapters, there will be many examples drawn from practical experience managing linguistic data, including data that has been collected in the course of linguistic fieldwork, laboratory work, and web crawling.The TIMIT corpus of read speech was the first annotated speech database to be widely distributed, and it has an especially clear organization.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.Finally, TIMIT includes demographic data about the speakers, permitting fine-grained study of vocal, social, and gender characteristics.