![\"\"](\"http:\/\/www.decisionsciencenews.com\/wp-content\/uploads\/2012\/01\/dgtsnd1.png\" "\\"dgtsnd\\"")
<\/a><\/p>\nAt Decision Science News, we have all kinds of numbers memorized: IP addresses, passport numbers, phone numbers, bank account numbers, logarithms, etc. Once you have stuff like this memorized, you’ll\u00a0 realize how much of a hassle it was to look all this stuff up all the time. Besides, it’s fun.<\/p>\n
But how is it done?<\/p>\n
It is done with the digit-sound method, which we learned from Professor Jaap Murre’s neuroMod site at the University of Amsterdam<\/a>. According to Murre, this amazing method traces back to 1648!<\/p>\n You associate a digit with a sound or sounds like this<\/p>\n 0<\/strong> z, s, soft-c ‘z’ is the first letter of zero Then, when you want to remember a number, you simply replace the digits with sounds and try to make a vivid phrase. Any vowels or sounds not included in the chart are ignored when you are reading back the phrase. For example, suppose you want to memorize Jenny’s phone number: 867-5309.<\/p>\n Here’s how we might do it:<\/p>\n We came up with the following dialog involving a parent and child at the dinner table:<\/p>\n –“Fish, ok?” In this mini play, we have “f”, “sh”, “k” “l”, “m”, “s” and “b” in order, and can easily reconstruct 867-5309. Remember, when reading it back, you ignore all vowels and letters that aren’t in the chart.<\/p>\n The only start-up cost is memorizing the chart, but that’s not hard. There’s even a training tool<\/a> so you can practice until you have the associations down pat.<\/p>\n Of course, since there can be a few possible sounds for each letter, you need to play around a bit to find a phrase that works for you. To generate possibilities for long numbers, we’ve written the following python <\/a>script.<\/p>\n NOTE 1: In this code, we’ve simplified the digit-sound method to include fewer letters since we always get confused with hard vs soft letters. We find the simplified method works just fine for us. Photo credit: http:\/\/memory.uva.nl\/memimprovement\/eng\/phon_peg_1.htm<\/span><\/p>\n","protected":false},"excerpt":{"rendered":" At Decision Science News, we have all kinds of numbers memorized: IP addresses, passport numbers, phone numbers, bank account numbers, logarithms, etc. Once you have stuff like this memorized, you’ll start to realize how much less of a hassle it is to have things in memory rather than on paper or disk. Besides, it’s fun.<\/p>\n But how is it done?<\/p>\n It is done with the digit-sound method, which we learned from Professor Jaap Murre’s neuroMod site at the University of Amsterdam.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","enabled":false}}},"categories":[4,16,2],"tags":[312,20,314,318,22,203,311,310,317,313,315,319,36,78,316],"class_list":["post-3023","post","type-post","status-publish","format-standard","hentry","category-encyclopedia","category-ideas","category-research-news","tag-cognition","tag-decision-making","tag-digit","tag-digit-sound","tag-heuristics","tag-judgment","tag-learning","tag-memory","tag-method","tag-mnemonic","tag-phonetic","tag-phonetic-mnemonic","tag-psychology","tag-rules","tag-sound"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p4LKj-ML","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/posts\/3023","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3023"}],"version-history":[{"count":29,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/posts\/3023\/revisions"}],"predecessor-version":[{"id":3054,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/posts\/3023\/revisions\/3054"}],"wp:attachment":[{"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3023"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3023"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3023"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\n1<\/strong> t, th, d ‘t’ has one downstroke
\n2<\/strong> n ‘n’ has two legs (downstrokes)
\n3<\/strong> m ‘m’ has three legs (downstrokes)
\n4<\/strong> r ‘r’ is the last sound in fouR
\n5<\/strong> l ‘l’ or L is the Roman numeral 50
\n6<\/strong> soft-g, j, sh, ch ‘g’ when turned around gives ‘6’
\n7<\/strong> k, q, hard-c, hard-g ‘k’ is made of two 7’s back-to-back
\n8<\/strong> f, v ‘f’ when written in script looks like ‘8’
\n9<\/strong> p, b ‘p’ when turned around gives ‘9’<\/p>\n\n
\n–“Lame! *sob*”<\/p>\n
\nNOTE 2: This code is written in a hackish, randomized way that generates wasteful dupes. However, we don’t care since it doesn’t output the dupes, it runs super fast, and if you have a huge number of possibilities, you don’t want to see them all anyway. That said, if people have better implementations, we’re open for suggestions. Thanks to Dan Reeves<\/a> for tightening up the code a bit!
\nNOTE 3: You can take the output of this program and hunt for words that fit the patterns with a linux call like this.
\ngrep -E ‘^l[aieouy]*m[aieouy]*n[aeiouy]*$’ wordlist.txt
\nWhere you are looking for words that match “l”, “m”, “n” and wordlist.txt is a list of words, one per line. You can find many wordlists here<\/a>.<\/p>\n#Usage. Save this file as generate.py\r\n#Then to use, do generate.py 867 (if 867 is the number for\r\n#which you want to generate letters)\r\nfrom cStringIO import StringIO\r\nimport random\r\nfrom sys import argv\r\nfrom time import strftime\r\nmstr=str(argv[1])\r\ndef genString():\r\n numsounds = [['s','z'], ['t','th','d'],['n'],['m'],['r'],\\\r\n['l'],['j','ch','sh',],['k','q'],['f','v'],['p','b']]\r\n return [random.choice(numsounds[int(i)]) for i in mstr]\r\ni=0\r\nmyDict={}\r\nwhile i<10000:\r\n astr=' '.join(genString())\r\n if not myDict.has_key(astr):\r\n myDict[astr]=1\r\n print '%-20s ==> %2d : %20s' % \\\r\n(astr,i,strftime(\"%Y-%m-%d %H:%M:%S\"))\r\n i=i+1\r\n\r\n<\/pre>\n