CASPR Research Report 2007-03 CPIDR 3 USER MANUAL
Contents
1. are acceptable Un Basic operation When CPIDR 3 is installed a shortcut to it is placed in your Programs menu When you launch CPIDR 3 there will be a one to three minute pause while the MontyLingua tagger is loaded and configured During this time a splash screen giving basic information about CPIDR 3 is displayed The main CPIDR screen looks like this CPIDR Manual Page 3 NN CPIDR 3 2 2694 23562 File Window Help Analyze Typed Input Analyze File s Save Results Denis C Speech mode reject repetitions fillers and hesitation forms CPIDR 3 2 2694 23562 Type or paste input here Results CPIDR 3 2 2694 23562 Mode Ideas Words Density Operation is fairly self explanatory Type one or more sentences into the white box or paste them from the clipboard and click Analyze Typed Input or else place your input in text files and choose Analyze File s In the latter case you are allowed to select multiple files and they will be processed in alphabetical order by full path and filename Here is an example of the analysis of a sentence ON CPIDR 3 2 2694 23562 File Window Help Analyze Typed Input Analyze File s m Save Results noes C Speech mode reject repetitions fillers and hesitation forms CPIDR 3 2 2694 23562 The authors of CPIDR thank you for your support The authors of CPIDR thank L 201 DT Ww the Results CPIDR 3 2 2694 23562 Mode Ideas Words De2. MA 275 528 532 Turner A and Greene E 1977 The construction and use of a propositional text base Technical report 63 Institute for the Study of Intellectual Behavior University of Colorado Boulder
3. The University of Georgia ARTIFICIAL INTELLIGENCE CENTER CASPR Research Report 2007 03 CPI DR 3 USER MANUAL Michael A Covington ad Caspr E COMPUTER ANALYSIS OF SPEECH FOR PSYCHOLOGICAL RESEARCH Artificial Intelligence Center The University of Georgia Athens Georgia 30602 7415 U S A www ai uga edu caspr 2007 CPIDR 3 User Manual Michael A Covington Artificial Intelligence Center The University of Georgia 2007 August 17 Introduction CPIDR 3 Computerized Propositional Idea Density Rater third major version is a computer program that determines the propositional idea density of an English text automatically It is well known that propositional idea density in the sense of Kintsch 1974 and Turner and Greene 1977 can be approximated by the number of verbs adjectives adverbs prepositions and conjunctions divided by the total number of words Snowdon et al 1996 In an earlier paper Brown et al 2007 we refined this technique and used a part of speech tagger plus adjustment rules to obtain accurate idea density measures CPIDR 3 is the latest product of this research program Authorship and version history The name CPIDR has been applied to several programs e A prototype idea density rater implemented in Prolog by Cati Brown e AJava program implemented by Tony Snodgrass using a somewhat more sophisticated rule set Brown et al 2007 e Thesame program ported to C by the s
4. ame author and using the same rule set CPIDR 2 e The current C program coded by Michael A Covington and using a considerably refined rule set CPIDR 3 described further by Brown et al in preparation CPIDR Manual Page 2 CPIDR 3 is a product of the CASPR project Computer Analysis of Speech for Psychological Research at The University of Georgia It is distributed as open source freeware under the General Public License see the file LICENSE TXT distributed with CPIDR for particulars CPIDR includes two additional open source components MontyLingua Liu 2004 and IKVM Frijters 2004 and inherits GPL from MontyLingua A future version of CPIDR will be self containined not relying on MontyLingua or IKVM For scientific integrity when using CPIDR in research you should always give the exact version and date which are displayed when you select Help About CPIDR in the main menu The version is also written at the beginning of each saved output file Installation requirements CPIDR 3 runs on any Windows 2000 XP or Vista system with NET Framework 2 0 installed To install CPIDR simply launch the supplied MSI file During installation you will be prompted to download NET Framework 2 0 from Microsoft if you do not already have it As input CPIDR 3 accepts ASCII or Unicode text files or input typed on the keyboard or pasted from the Windows clipboard Smart quotes the characters as well as ASCII quotes
5. der and 53 refusing to come to the party In Turner and Greene s sentence 46 J immy ate an orange and a banana the MontyLingua tagger mistakenly tags orange as an adjective leading CPIDR 3 to count an extra proposition References Brown Cati Snodgrass Tony Covington Michael A Herman Ruth Kemper Susan J 2007 Measuring propositional idea density through part of speech tagging Poster presented at Linguistic Society of America Anaheim California Available at http www ai uga edu caspr Brown Cati Snodgrass Tony Kemper Susan J Herman Ruth and Covington Michael A in preparation Automatic measurement of propositional idea density from part of speech tagging CPIDR Manual Page 7 Frijters J eroen 2004 IKVM an implementation of J ava for Mono and the NET Framework http www ikvm net and SourceForge Kintsch W A 1974 The representation of meaning in memory Hillsdale NJ Erlbaum Liu Hugo 2004 MontyLingua An end to end natural language processor with common sense http web media mit edu hugo montylingua Santorini Beatrice 1995 Part of speech tagging guidelines for the Penn Treebank Project 3 revision University of Pennsylvania Snowdon D A Kemper S J Mortimer J A Greiner L H Wekstein D R and Markesbery W R 1996 Linguistic ability in early life and cognitive function and Alzheimer s disease in late life Findings from the Nun Study J A
6. es cs which is installed with CPIDR 3 in the src folder This file is copiously commented so that non programmers can read it Many of the rules condense complicated verb phrases into single propositions For example may have been singing is just one proposition following Turner and Greene 1977 who do not treat tense or modality indicators as propositions May not have been singing is two propositions not five Subject aux inversion is undone in order to handle questions correctly For example Has he resigned is changed to he has resigned so that subsequent rules handling has resigned will apply In the Details window this is displayed as CPIDR Manual Page 6 Has he resigned 002 has moved 002 PRP W he 402 VBZ W has 200 VBD W P resigned eee indicating the original and moved positions of has In some cases an auxiliary verb moves too far for example Is he president is changed to he president is but the proposition count is still correct The accuracy of CPIDR 3 For detailed tests of CPIDR 3 see Brown et al in preparation CPIDR 3 agrees entirely with the proposition counts given by Turner and Greene 1977 for all but three of their 69 example sentences CPIDR 3 always counts Verb Preposition Noun Phrase as two propositions treating come to Boston exactly like sing in Boston Turner and Greene usually do the same but they do not count to as a proposition in their sentences 2 Fred went to Boul
7. nsity Norm 4 9 0 444 The authors of CPIDR thank you fo authors of 200 PRP W P your 002 NN W Support 000 4 propositions 9 words 0 444 density CPIDR Manual Page 4 The Results window shows the idea count proposition count word count idea density and an identifying string the first 37 characters of the text or if the text had some from a file the filename As you analyze more sentences and files more lines are added to this window The Details window shows you how the sentence was analyzed The authors of CPIDR thank you for your support 201 DT W the 002 NNS W authors 200 IN W P of 002 NNP W cpidr 200 VB W P thank 002 PRP W you 200 IN W P for 200 PRP W P your 002 NN W support eee Here 000 002 200 and 201 are the rules in CPIDR s rule set that acted upon each word DT NNS IN etc are part of speech tags W and P indicate which items were counted as words and as propositions We recommend that you look briefly at the Details window to make sure words and propositions are being counted correctly Speech mode If you check Speech mode in the main window CPIDR will reject most repetitions i e will not count them as new propositions though they remain in the word count and will reject hesitation forms and interjections more aggressively as is appropriate for unedited transcribed speech How to save results to a file The Save Results button lets you save the c
8. ontents of the Results window as a tab delimited text file suitable for importing into Excel The Save Details button saves the detailed analysis onto a file You can also use the mouse and right mouse button to copy material from the Results or Details window to the clipboard then paste it into another program CPIDR Manual Page 5 On the main menu Window Clear Output Windows clears all the displayed results so that you can start afresh How CPIDR 3 works The premise of CPIDR 3 is that although it is roughly correct to equate every verb adjective adverb conjunction and preposition with an idea proposition numerous readjustment rules are needed to get an accurate count CPIDR 3 does not understand every sentence in full and therefore does not produce perfect proposition counts but it has been shown to be more reliable than most if not all human raters The part of speech tags are those of the Penn Treebank Santorini 1995 not later versions The most important ones are sentence ending punctuation CC coordinating conjunction CD cardinal number DT determiner IN preposition except to JJ JJR JJS adjective positive comparative superlative MD modal verb NN NNS noun singular plural RB RBR RBS adverb positive comparative superlative TO to preposition or infinitive VB VBZ VBD VBN VBG verb various forms The full set of readjustment rules is documented in the file IdeaDensity RaterRul
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