______________________________________________________________

• Programmer: Farhan Bin Faisal
• Files: preprocess.ipynb, wordListMaker.m, postWuggy.ipynb, generateConditions.ipynb
• Date Created: 10 November 2022
• Meltzer Lab

______________________________________________________________

RESEARCH POSTER

______________________________________________________________

EXPERIMENT PARADIGM

The NBAck Training paradigm was programmed in JavaScript (using PsychoJS) and hosted on Pavlovia. A trial run can be accessed here. Please input the following credentials

• session: 1
• participantID: 19995

______________________________________________________________

STIMULY GENERATION PIPELINE

1.) preprocess.ipynb

• Loads word csv file into a pandas dataframe
• Filters rows for frequency (4.0 Zipfvalue < 5.0)
• Gets syllables of each word
  • Uses cmu_dict from nltk
• Filters rows for syllables (1 < syllable < 2)
• Replaces each word with its corresponding lemma
  • Uses WordNetLemmatizer for this
• Discards rows not found in cmudict
• Discards profane words and names
• Formats dataframe into SOS-compatible input
• Outputs dataframe as a tab delimited txt file
  • File Named "sos_input.txt"

______________________________________________________________

2.) wordListMaker.m

• Uses SOS to make 18 lists of 10 words each
• Lists matched on ZipfValue and syllables
  • Used soft constraints for this
  • Used hard constraints to floor syllable count and frequency
• Lists can be found in the folder "wordLists"

______________________________________________________________

3. a) wuggy/postSOS.ipynb

• Generates nonword lists for every wordList
• nonWordLists outputted to folder nonWordList
• Prints filenames of files which contain words that could not be converted to a nonWord automatically
  • Need to generate those pseudowords manually

______________________________________________________________

3. b) Wuggy || Generate nonWords manually

• Download from http://crr.ugent.be/programs-data/wuggy
• Settings used:
  • Orthographic English
  • Match syllable length
  • Match word length
  • Match transition frequency
  • Match 2 out of 3 segments
• Manually pass the words that could not be found in the lexicon through Wuggy