As its name implies, the AwesomeTTS Anki add-on is awesome. It’s nearly indispensable for language learners.
You can use it in one of two ways:
Subscribe on your own to the text-to-speech services that you plan to use and add those credentials to AwesomeTTS. (à la carte) Subscribe to the AwesomeTTS+ service and gain access to these services. (prix fixe) Because I had already subscribed to Google and Azure TTS before AwesomeTTS+ came on the scene, there was no reason for me to pay for the comprehensive prix fixe option.
Most language learners are familiar with Forvo, a site that allows users to download and contribute pronunciations for words and phrases. For my Russian studies, I make daily use of the site. In fact, to facilitate my Anki card-making workflow, I am a paid user of the Forvo API. But that’s where the trouble started.
When the Forvo API works, it works OK, often extremely slow. But lately, it has been down more than up.
Recently, someone asked a question on r/Anki about changing and existing cloze-type note to a regular note. Part of the solution involves stripping the cloze markup from the existing cloze’d field. A cloze sentence has the form Play {{c1::studid}} games. or Play {{c1::stupid::pejorative adj}} games.
To handle both of these cases, the following regular expression will work. Just substitute for $1. {{c\d::([^:}]+)(?:::+[^}])}}
However, the Cloze Anything markup is different. It uses ( and ) instead of curly braces.
I make a lot of Anki cards, so I’m on a constant quest to make the process more efficient. Like a lot of language-learners, I use images on my cards where possible in order to make the word or sentence more memorable.
Process When I find an image online that I want to use on the card, I download it to ~/Documents/ankibound. A Hazel rule then grabs the image file and converts it to a .
Anki users are protective of their streak - the number of consecutive days they’ve done their reviews. Right now, for example, my streak is 621 days. So if you miss a day for whatever reason, not only do you have to deal with double the number of reviews, but you also deal with the emotional toll of having lost your streak.
You can lose your streak for one of several reasons.
Welcome to Part III of a deep dive into my Anki language learning decks. In Part I I covered the principles that guide how I setup my decks and the overall deck structure. In the lengthy Part II I delved into my vocabulary deck. In this installment, Part III, we’ll cover my sentence decks.
Principles First, sentences (and still larger units of language) should eventually take precedence in language study. What help is it to know the word for “tomato” in your L2, if you don’t know how to slice a tomato, how to eat a tomato, how to grow a tomato plant?
In Part I of my series on my Anki language-learning setup, I described the philosophy that informs my Anki setup and touched on the deck overview. Now I’ll tackle the largest and most complex deck(s), my vocabulary decks.
First some FAQ’s about my vocabulary deck:
Do you organize it as L1 → L2 or as L2 → L1, or both? Actually, it’s both and more. Keep reading. Do you have separate subdecks by language level, or source, or some other characteristic?
Although I’ve been writing about Anki for years, it’s been in bits and pieces. Solving little problems. Creating efficiencies. But I realized that I’ve never taken a top-down approach to my Anki language learning system. So consider the post the launch of that overdue effort.
Caveats A few caveats at the outset:
I’m not a professional language tutor or pedagogue of any sort really. Much of what I’ve developed, I’ve done through trial-and-error, some intuition, and a some reading on relevant topics.
For one-off projects that target Anki collections, I often use Python in a standalone application rather than an Anki add-on. Since I’m not going to distribute these little creations that are specific to my own needs, there’s no reason to create an add-on. These are just a few notes - nothing comprehensive - on the process.
One thing to be aware of is that there must be a perfect match between the Anki major and minor version numbers for the Python anki module to work.
One of the things that I love about Keyboard Maestro is the ability to chain together disparate technologies to achieve some automation goal on macOS.
In most of my previous posts about Keyboard Maestro macros, I’ve used Python or shell scripts, but I decided to draw on some decades-old experience with Perl to do a little text processing for a specific need.
Background I want this text from Wiktionary:
to look like this: