Projects tagged ‘french’ and ‘python’

MangerSain is a food additives application for mobile devices (specialy written for the Openmoko Neo Freerunner). Its interface aims to be easy and finger friendly. It's written in Python / ... [More] Elementary and uses SQLite for storing data. MangerSain allows you to consult easily and quickly a list of food additives and their toxicity. Data are in French only and come from the site http://mangersain.medicalistes.org. [Less]

Software to learn languages: Dutch, English, Spanish, French, etc Mainly Grammar and Vocabulary First versions would be only in text mode. Written in Python and wxpython. All code is published ... [More] under GPL All documentation and algorithms are published under GFDL See the wiki tab for more information Developper : Oualmakran Youssef, aka youssefsan . More about Youssef on http://fr.wikipedia.org/wiki/Utilisateur:Youssefsan The name omniglossia is an idea from Francis Tyers who kindly suggested me to use the name for the project. Java tools for ApertiumThe goal is to exctract data from the Apertium xml dictionaries (Apertium is at http://xixona.dlsi.ua.es/wiki/index.php/Main_Page) and to make two seperate files. I focus first on Dutch nouns. The frist file will be with nouns in the form masculin of feminin or neuterfoofoos. The other will be with paradigms. ... ... ... ... With singular = root + singular_ending and plural = root + plural_ending News2007 9 September: Adding Java tools to extract data from the Apertium monodixes.(Apertium is at http://xixona.dlsi.ua.es/wiki/index.php/Main_Page) 26 March: the algorithm for saying the time in Ducth is already published on the wiki. Source code has not been published yet. I must learn how to use svn. The python code does not yet anything very useful yet. Related softwareYou may also visit - http://apertium.sourceforge.net, a site of open source machine software translation. - http://sensmotdire.gnunux.info/, French verbs [Less]

Find the best e-commerce et crm solution in Python.

Projects and informations by Kedare (Mathieu Poussin)Languages Used :Python ActionScript3/Flex

Leximnesiaby Florian Mortgat There is now an official website: http://leximnesia.org Leximnesia is a very simple, efficient software: it asks questions and the user answers them (either in his ... [More] head or in a text entry). Then the software gives the right answer and so forth. The only thing is that the questions he answered wrongly will be re-asked and re-asked until he knows the right answer perfectly. See the FAQ. InstallingFor Windows usersYou need to install python, then leximnesia. Python installer is available here Leximnesia installer is available here. For Linux usersYou probably know how to do: go to the download section, download, unpack the archive and follow the instructions. For Mac OS X usersThe archive is the same as for Linux, but I must admit I tried only once under Mac OS and it was buggy because the default python version was too old (2.3). The GUI worked but the asked question was always the same, due to a bug in python classes inherited from lists in 2.3. I suppose it would work if you install python 2.4 or 2.5. The installation procedure is the same as for Linux. FeaturesYou can use the existing question files and learn about 3000 words of German (for French people), 1000 words of English (for French people) and 500 words of French (for German people). There are two ways to use the software: a "quick mode", which involves no typing but requires you to be honest and tell the computer when the answer you thought of was wrong and a "slower mode", in which you type the answer. The computer will correct it automatically. It is also: very easy to modify a question (for example to add a new accepted answer) possible, quick and easy to add new questions to an already-existent question file possible and not very difficult to create new question files. [Less]

This system uses probabilistic techniques to estimate a user's knowledge and intelligently ask different flashcard definitions. The problem is represented as such: At each point in time there is a ... [More] probability distribution describing a user's chance of defining a word correctly. By asking the user to provide the definition, you observe that distribution. Then telling the user that they are right or wrong affects the distribution. The probability distribution for a user to correctly answer each word is calculated via particle filtering. The resultant change in probability distribution from answering a definition is learned, and assumed to be dependent upon: previous probability of answering correctly, whether the user answered correctly, and how long it had been since the word had been previously asked. Thus a user is (hypotheticly) likely to learn more if frequently asked a word, and the amount learned varies depending on how well they already know the word. With that probabilistic reasoning in place, a value function is defined for probability distributions. The program then finds it very valuable to know a word well, and painful to know a word poorly. The program then selects the next word to ask by greedily choosing the word that is most likely to increase the total value function (probabilistically of course). The implementation is in python, still slow, lacks a GUI, and could use some more words to ask (I have learned them all through debugging . . .). The program architecture still needs to be fitted with the idea of a 'working set' of words, which define those over which the value function is computed. Thus, the program is able to ask the user new words incrementally rather than the entire dictionary at once. [Less]