Skip to main content
Datasets used to train and test the Cortical Spectro-Temporal Model (CSTM)
Computer Science: Faculty Publications and Other Works
  • Dario Dematties, University of Buenos Aires
  • George K. Thiruvathukal, Loyola University Chicago
  • Silvio Rizzi, Argonne National Laboratory
  • Alejandro Javier Wainselboim
  • Bonifacio Silvano Zanutto, University of Buenos Aires
Document Type
Data Set
Publication Date
Publisher Name

ZIP files of folders containing all the datasets (audio file corpora) employed in our research to train the Encoder Layer (EL) and the SVMs and to test the complete CSTM. This folder includes a set of 840 corpora which are distributed in 2 corpora for each configuration organized by 2 sets of synthesized voices, 3 syllabic conditions (i.e. mono-, di- and tri-syllabic English words) and 10 completely different vocabularies all distributed in 6 acoustic variants, beyond the original version of the corpora.

The 6 acoustic variants corresponds to: two levels of white noise (19.8 dB and 13.8 dB Signal to Noise Ratio (SNR) average Root Mean Square (RMS) power rate), two levels of reverberation (Reveberation-Time 60 dB (RT-60) value of 0.61 seconds and 1.78 seconds) and variations of pitch on both directions (from E to G and from E to C).

Creative Commons License
Creative Commons Attribution-Noncommercial-No Derivative Works 3.0
Citation Information
Dematties, Dario, Thiruvathukal, George K., Rizzi, Silvio, Wainselboim, Alejandro Javier, & Zanutto, Bonifacio Silvano. (2019). Datasets used to train and test the Cortical Spectro-Temporal Model (CSTM). (Version v1.0) [Data set]. Zenodo.