Dataset for file fragment classification of audio file formats

Atieh Khodadadi, Mehdi Teimouri
BMC Research Notes 2019 December 21, 12 (1): 819

OBJECTIVES: File fragment classification of audio file formats is a topic of interest in network forensics. There are a few publicly available datasets of files with audio formats. Therewith, there is no public dataset for file fragments of audio file formats. So, a big research challenge in file fragment classification of audio file formats is to compare the performance of the developed methods over the same datasets.

DATA DESCRIPTION: In this study, we present a dataset that contains file fragments of 20 audio file formats: AMR, AMR-WB, AAC, AIFF, CVSD, FLAC, GSM-FR, iLBC, Microsoft ADPCM, MP3, PCM, WMA, A-Law, µ-Law, G.726, G.729, Microsoft GSM, OGG Vorbis, OPUS, and SPEEX. Corresponding to each format, the dataset contains the file fragments of audio files with different compression settings. For each pair of file format and compression setting, 210 file fragments are provided. Totally, the dataset contains 20,160 file fragments.

Full Text Links

Find Full Text Links for this Article


You are not logged in. Sign Up or Log In to join the discussion.

Related Papers

Remove bar
Read by QxMD icon Read

Save your favorite articles in one place with a free QxMD account.


Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"