Building on my earlier explorations of the UDAR project, I’ve created a macOS Service-like method for in-situ marking of syllabic stress in arbitrary Russian text. The following video shows it in action:
The Keyboard Maestro is simple; we execute the following script, bracketed by Copy and Paste:
#!/Users/alan/.pyenv/shims/python3 import xerox import udar import re rawText = xerox.paste() doc1 = udar.Document(rawText, disambiguate=True) searchText = doc1.stressed() result = re.sub(r'( ,)', ",", searchText) xerox.
After installing Stanza as dependency of UDAR which I recently described, I decided to play around with what is can do.
Installation The installation is straightforward and is documented on the Stanza getting started page.
First,
sudo pip3 install stanza Then install a model. For this example, I installed the Russian model:
#!/usr/local/bin/python3 import stanza stanza.download('ru') Usage Part-of-speech (POS) and morphological analysis Here’s a quick example of POS analysis for Russian.
One of the challenges that Russian learners face is the placement of syllabic stress, an essential determinate of pronunciation. Although most pedagogical texts for students have marks indicating stress, practically no tests intended for native speakers do. The placement of stress is inferred from memory and context.
I was delighted to discover Dr. Robert Reynolds' work on natural language processing of Russian text to mark stress based on grammatical analysis of the text.
In a previous post I described macros to support certain tasks in generating source material for L2 chorus repetition practice. Today, I’ll describe two other macros that automate this practice by slowing the playback speed of the repetition.
Background I’ve described the rationale for chorus repetition practice in previous posts. The technique I describe here is to slow the sentence playback speed to give the learner time to build speed by practicing slower repetitions.
Achieving fluid, native-quality speech in a second language is difficult task for adult learners. For several years, I’ve used Dr. Olle Kjellin’s method of “chorus repetition” for my Russian language study. In this post, I’m presenting a method for scripting Audacity to facilitate the development of audio source material to support his methodology.
Background For detailed background on the methodology, I refer you to Kjellin’s seminal paper “Quality Practise Pronunciation with Audacity - The Best Method!
This is an update to my previous post on automating iTunes on macOS to support chorus repetition practice. You can read the original post for the theory behind the idea; but in short, one way of developing prosody and quality pronunciation in a foreign language is to do mass repetitions in chorus with a recording of a native speaker.
Because in macOS 10.15, iTunes is no more, I’ve updated the script to work with the new Music app.
I’ve recently discovered the L-R system of language learning and have been setting up to learn it.
The idea is that you begin with long texts - novels, for example - in your target language (L2) and follow a systematic approach to reading and listening.
L-R system in a nutshell Here are the steps:
Read the text in L1 (your native language) and become familiar with it.^[I rephrased this intruction from other sources that say “read the translation” because what if the text itself if a translation?
Regex 101 is a great online regex tester.
Speaking of regular expressions, for the past year, I’ve used an automated process for building Anki flash cards. One of the steps in the process is to download Russian word pronunciations from Wiktionary. When Wiktionary began publishing transcoded mp3 files rather than just ogg files, they broke the URL scheme that I relied on to download content. The new regex for this scheme is: (?
