In one week the Gamify project has gotten roughly 700 participants from around the world, including Kazakstan!
Of the new visitors (which we assume are coming to play for the first time) they are averaging 3.4 pages per visit, most are completing the experiment, which takes an average of 5 minutes to complete. We won’t know for a few weeks how many of the participants have usable data.
Surprisingly, we had a few installs on the Android Market, many of whom also went through all three stages of the game.
Emmy and Hisako are proud to present the release of Spy or Not, a gamified psycholinguistics experiment made in collaboration with the Accents Research Lab at Concordia University headed by Dr. Spinu.
It is commonly observed that some people are “Good with Accents.” Some people can easily imitate various accents of their native language, while others appear struggle with imitation. This research is dedicated to building free OpenSource phonetics scripts to extract the acoustic components of native speakers and “Good with Accents” speakers to transfer the technical details in a visualizable format to applied linguists on the ground who are working with accented (clinical and non-native) speakers.
In order to collect non-biased judgements from native speakers, a pilot study was designed and run by Dr. Spinu and her students. Images and supporting sound effects were created and the perceptual side of the pilot was disguised as the game “Spy or Not?” The game has since gathered over 8,000 data points by crowdsourcing the judgements to determine the degree (on an 11 point scale) of which participants were “Good with Accents.” This a novel approach to the coding problems that experimenters frequently encounter.
Participation in this project furthers research in phonetics and phonology in addition to experimental methodology in the age of the social web. Our hope is that our readers will Tweet their “Good with Accents” scores and help us get more participants, especially native speakers of Russian English accents, Sussex English accents and South African accents, accents we could never access at the scale we need in a lab setting. Visit the free online game, or play offline by downloading the game at the Chrome Store or on Google Play as a Android App.
If you have a spell checker, you want it to suggest a number of words that are close to the misspelt word. For humans, its easy for us to look at ‘teh’ and know that it is close to ‘the’, but how does the computer know that? A really simple Language Independent way to do it if you don’t have any gold standard data, is to assign costs to the various edits, substitution (2), deletion (1) and insertion (1), and picking the cheapest one.
The table below applies Levenshtein’s algorithm (basically, substitution costs 2) letter by letter. The total distance between the two words, 4 is in the top right corner, because it costs 2 to substitute ‘u’ for ‘i’ and 2 to substitute ‘t’ for ‘k’.
And if you really like it, you can download it from github. Click here to read more about edit distance.