Analysis and data manegent for the audio descriptors study.
descriptors_{date}.csv is the current edited survey data. qualtrics_raw.csv is the data file directly from qualtrics. SoundDescriptorsParsed.xlsx stores the official tags list for the literature and survey corpora.
- Requirements listed in requirements.txt file
- Tested on Windows 10 / Linux
pip install -r requirements.txt
python statistics.py
Results will look something like:
-------------- SURVEY STATS --------------
STAT VALUE
-----------------------------------------------
total responses 95.00
completion count 28.00
abandon count 67.00
completion rate % 29.47
average completion time (m) 128.75
min completion time (m) 4.33
max completion time (m) 1324.68
trim mean completion time (m) 23.06
empty questions [1, 6, 27, 72]
-------------- SURVEY TAG STATS --------------
STAT VALUE
-----------------------------------------------
total tags 1072.00
total unique tags 661.00
total unique tag/class pairs 724.00
total descriptor tags 585.00
unique descriptor tags 409.00
total emotion tags 487.00
unique emotion tags 315.00
tags described as both 63.00
% tags in dictionary 93.80
% words in lit words 10.59
% not in lit words 89.41
-------------- LITERATURE TAG STATS --------------
STAT VALUE
-----------------------------------------------
total tags 232.00
% words in survey tags 30.17
% words not in survey tags 69.83
-------TAGS IN BOTH EMOTION AND DESCRIPTOR---------------
{'quick', 'shrill', 'light', 'powerful', 'scary', 'jarring', 'edgy', 'noisy', 'happy', 'annoying', 'warm', 'warning', 'busy', 'smooth', 'rhythmic', 'close', 'calming', 'natural', 'surprised', 'soft', 'chill', 'sharp', 'dynamic', 'conversational', 'mechanical', 'abrasive', 'blaring', 'dangerous', 'alarm', 'comfortable', 'expectant', 'urgent', 'mellow', 'uplifting', 'exciting', 'bright', 'playful', 'loud', 'awful', 'strident', 'on-edge', 'urgency', 'watery', 'ominous', 'falling', 'nature', 'empty', 'harmonious', 'dark', 'alarming', 'angry', 'energetic', 'futuristic', 'alert', 'artificial', 'fast', 'chaotic', 'grainy', 'hollow', 'movement', 'naturalistic', 'moist', 'enticing'}
-------MOST COMMON SURVEY TAGS------------
[('synthetic', 13), ('sharp', 12), ('bright', 12), ('annoying', 10), ('alarming', 10), ('exciting', 9), ('peaceful', 9), ('abrasive', 8), ('tense', 8), ('scary', 8)]
python write_tensors.py
Survey responses only:
- tags_survey.tsv
- tensors_survey.tsv
Survey responses and literature descriptors:
- tags_all.tsv
- tensors_all.tsv
Survey responses with correlated question numbers:
- tags_questions.tsv
- tensors_questions.tsv
Output files stored in the outputfiles directory.
Plot here: https://projector.tensorflow.org/ Select the tensors file for vectors, and the corresponding tags file for metadata.
Run this file each time we collect new descriptor data in the qualtrics_edited.csv file. View the definitions in the DescriptorsLibrary.xlsx file on the Survey Descriptors sheet.
python definitions.py
Joshua Kranabetter
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent