Datasets used to train and test the Cortical Spectro-Temporal Model (CSTM)

Dario Dematties, George K. Thiruvathukal, Silvio Rizzi, Alejandro Javier Wainselboim, Bonifacio Silvano Zanutto

Research output: Non-textual formDigital or Visual Products

Abstract

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).

Original languageAmerican English
Media of outputOnline
StatePublished - Mar 1 2019

Disciplines

  • Artificial Intelligence and Robotics
  • Computer Sciences

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