Dataset size considerations for robust acoustic and phonetic speech encoding models in eeg

HIGHLIGHTS

• who: Maansi Desai from the University of Salzburg, Austria have published the paper: Dataset size considerations for robust acoustic and phonetic speech encoding models in EEG, in the Journal: (JOURNAL)
• what: The authors provide methods to assess whether such data may be usable and whether receptive field results are stable. The authors provide suggestions in assessing the amount of training data needed if one were to use a single feature representation (such as phonological features or the acoustic envelope or pitch) for specific stimuli vs. using a combination of all features (phonological features plus the . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or E-mail:

  If you don't have an account, you can create one here.