![]() It is as close as you'll get to GNU Emacs without compiling for yourself. It fits in well enough with the operating system, but at the same time, is the wonderful Emacs we all know and love. ![]() Currently it requires Leopard with the latest release, but most people have upgraded by now anyway. You can fetch it here.Īlternatively, if you want to use Vim on OS X, I've heard good things about MacVim.īeyond those, there are the obvious TextEdit, TextMate, etc line of editors. If not for computational analysis, maybe for that next German Diction assignment!Īnd we’ll always welcome new contributions to the dictionary.BBEdit makes all other editors look like Notepad.They work for some people, but most "advanced" users I know (myself included) hate touching them with anything shorter than a 15ft pole. However, having a translator that automatically generates IPA for a large number of words in each poem will certainly help us move a lot faster as we build our corpus of nineteenth-century German poems.įeel free to try out the script. There will always be some human intervention with the IPA text. So we’ll never be able to simply go straight from a German poem to statistical analysis of phonemical structures that are music- and stress-sensitive. For example, “und” might be stressed one time in the poem and unstressed the next. While multi-syllable words have stress patterns that we can encode in the dictionary, every poem has single-syllable words, and their poetic stress is dependent on the meter of the poem and the arrangement of words within that meter. There’s one thing that this translator won’t be able to do, though: stress. Then, every time we finish an IPA translation, we run the dictionary builder and add words to the dictionary, speeding up all of our subsequent translations in the process. However, in a future stage, we hope to write a dictionary builder - a script that will analyze fully translated songs for German-IPA word pairs and then add them to the dictionary. And as the dictionary grows, it will speed up the process even more.įor now, we’re adding words to the dictionary manually, focusing on those that are the most frequent in the poems we’re studying. However, even just getting 20% of the words out of the way will save a good chunk of time. Note that not every word is translated, only those in the dictionary. Here’s what the German text for “Nacht und Träume” looks like going into the script: Or if you use a program like TextMate for Mac to edit the file names in the script, simply save the script and type command-R to run it from within TextMate. At the terminal, run: python GermanToIPA.py Then go to the last three lines of the script and update the sourceFile and outputFile names to suit your needs. All you need is a text file with a German poem (here’s “Nacht und Träume” if you want a sample), the German-to-IPA dictionary, and this script. It even strips punctuation and accounts for capitalization. This script takes a text file containing a German poem, checks each word against Jordan’s German-to-IPA dictionary, and if the word is in the dictionary, it replaces it with its IPA equivalent. (Leigh has also created an ordered list of the most common words in Schubert’s songs which will serve as the basis for further growth of the dictionary.) Then this morning, Jordan, David, and I wrote a translator script in Python. To start, Jordan compiled a list of 50 of the most common words in German, along with their IPA translation. The IPA Unicode tool helps a lot, but translating German text to IPA, and then encoding that IPA as digital text, is a long, slow job. By far, the slowest part of this project is encoding the poetry in a way that allows us to analyze its sound computationally.
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