annajh/AD
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{\rtf1\ansi\ansicpg1252\cocoartf1404\cocoasubrtf340 {\fonttbl\f0\fnil\fcharset0 Menlo-Italic;} {\colortbl;\red255\green255\blue255;\red128\green128\blue128;} \paperw11900\paperh16840\margl1440\margr1440\vieww10800\viewh8400\viewkind0 \pard\tx560\tx1120\tx1680\tx2240\tx2800\tx3360\tx3920\tx4480\tx5040\tx5600\tx6160\tx6720\pardirnatural\partightenfactor0 \f0\i\fs24 \cf2 files:\ - dementia_features.txt: feature vectors for EACH VISIT of dementia population\ - control_features.txt: feature vectors for EACH VISIT of controls\ - dementia_features_combinedSubject.txt: feature vectors for EACH SUBJECT of dementia population\ - control_features.txt: feature vectors for EACH SUBJECT of controls\ \ Components of the feature vectors are as follows:\ 0. # of tokens\ 1. # of pronouns\ 2. # of adjectives\ 3. # of proper nouns\ 4. # of verbs\ 5. Type Token Ratio (TTR)\ 6. Brunet's Index (BI)\uc0\u8232 7. Honore's Statistics(HS)\ 8. % of pronouns\ 9. % of adjectives\ 10. % of proper nouns\ 11. % of verbs\ 12. # of filler words\ 13. % filler words\uc0\u8232 14. number_of_syllables\ 15. number_of_pauses\ 16. total_duration_of_audio\ 17. mean_pause_time\ 18. duration_of_voiced_time\uc0\u8232 19. speech_rate(#syllables/totalDuration)\ 20. articulation_rate(#syllables/voicedTime)\ 21. asd(voicedTime/#Syllables)\uc0\u8232 22. mean_length_utterance\ 23. standard_deviation\uc0\u8232 24. min_difference_in_f1&f2\ 25. max_difference_in_f1&f2\ 26. mean_difference_of_f1&f2\ 27. standard_deviation_of_difference\ }
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