Data set for (binary) text classification, involving spoken utterances and written text

This data set contains sentences belonging to either of two classes: Transcripts of spoken (informal) text (Class 0), and written, formal text (Class 1). Sentences in Class 0 were obtained from publicly available transcripts of radio shows (e.g. NPR), whereas Sentences in Class 1 were obtained from Wikipedia. The data set is divided into three subsets: Training, validation, and test (specified by the file names). Each set contains a large number of sentences, belonging to either of the two classes: In total, there are 13,640,458 sentences, of which 6,374,487 in Class 0 and 7,265,971. The training set contains 9.743,188 sentences (of which 4,553,205 in Class 0 and 5,189,983 in Class 1), the validation set contains 1,948,639 sentences (of which 910,641 in Class 0 and 1,037,998 in Class 1), and the test set contains 1,948,631 sentences (of which 910,641 in Class0 and 1,037,990 in Class1). The data sets are in plain text format. Every row contains (i) the class label (0 or 1) and (ii) the text of the sentence, separated from the class label by a tab character. Note that the sentences contain 5 tokens or more (including punctuation marks)

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See Also
article An interpretable method for automated classification of spoken transcripts and written text M. Wahde (Mattias), M.L. Della Vedova (Marco), M. Virgolin (Marco) and M. Suvanto (Minerva)