Tag: word frequency

Recently, I created a set of flashcards of single Chinese characters, to practice writing. The front of my Anki cards contained the pinyin, definition, and clozes for the most common words containing the character, while the back of the card was simply the character. I tagged the cards in groups of 200 by frequency rank, using tags of “1-200”, “201-400”, etc. I already know a number of characters, so I decided to start practicing with the more infrequent characters, the “1601-1800” tag.

There were some characters I was well familiar with. Other characters took more time to remember how to write, but weren’t too difficult, as I knew the characters on sight from extensive reading. But every once in a while I would be shown a card, and it would be for a character I had never seen before in 6 years! Some like 贼 (zéi, thief) or 鹏 (péng a mythical bird) were surprising to see in the 1600-1800 range for frequency ranks, ranked more frequent in the Lancaster Corpus than 垂 (chuí to hang down) and 夹 (jiā to squeeze). But however unusual they were, I still recall encountering them at some point (金色飞贼 is the golden snitch in Quidditch from Harry Potter, and 鹏 was from reading on Chinese mythical animals). However, 琉 (liú glazed tile) and 鲍 (bào abalone) don’t look familiar at all, and I am fairly certain I have never seen the characters 萼 (è calyx of a plant) and 懋 (mào diligent) in over 6 years of study. Is it just a strange chance that I haven’t encountered them, is it failing memory, or are they more rare than their frequency would suggest?

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The Lancaster Corpus of Mandarin Chinese as an SQL Database

In my Chinese studies, the Lancaster Corpus of Mandarin Chinese (LCMC) has been a useful source of data—word and character frequencies, collocations, phrase usage, parts of speech, etc. The corpus is freely available for non-commercial and research use. However, the native form of its data is in a set of XML files, which is not an easy format to work with. In addition, the XML data is slow to read data from, because all those XML tags and the entire data structure needs to be parsed. A much better format for the data is an SQL database. Stored in a database, many kinds queries and reports can be executed very efficiently. Depending on the software, these queries and reports can return results very quickly, much faster than in the XML format.

I have made available a Perl script and some other related tools to assist with extracting the LCMC files into a SQLite database. SQLite is a lightweight relational database management system intended for portability and ease of use. Because it functions as a standalone program (not client-server), it is easy to install and use. It’s more ubiquitous than you might think. It’s how the Firefox and Chrome browsers stores its history, cookies, and preferences. But it’s also used, for example, by the Anki program as the storage format for flashcard data, and by the Calibre e-reader program to store information on installed e-books.

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The HSK is a well-known skill level test used by the PRC to assess language proficiency in Chinese. Even for those who have no interest in taking the HSK test, the lists of Chinese words associated with the test are a convenient source of material for learners to study vocabulary. I have used these word lists myself with great success; it was a quick and effective way to gain a huge amount of usable vocabulary.

In 2010, the HSK exam underwent a major reworking, changing the structure of its skill ranks, increasing emphasis on speaking and writing, and revising its vocabulary. Where the “old” pre-2010 word lists consisted of 8,000+ words across 4 levels, the “new” HSK has 5,000 words distributed into 6 levels. Below is a summary of the word counts in the old and new vocabulary lists, based on actual word lists obtained from various sources (see footnotes for details). Note that these include a small amount of double counting (less than 2%) due to words repeated at more than one level, because of either different pronunciation or meaning. Also note that these counts differ slightly from the official word counts reported by Hanban.

Word counts in the old and new HSK word lists
Level old HSK new HSK
1 1007 153
2 2001 150
3 2189 300
4 3587 600
5 1300
6 2513
Total 8784 5016

Since I had invested so much time in studying the old lists (up to level 3), it was natural to wonder whether I should continue studying my existing flashcards or switch to the new HSK lists. How many words have I learned that are deprecated by the HSK, and does it mean they are unimportant? If I did switch, what level should I pick to start studying ?

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Hapax Legomena vs. the Brick Wall

The Brick Wall

With reading as my primary skill of focus in learning Chinese, a large part of my study is acquiring new words. Some vocabulary is from general word lists such as the HSK, while much of it is tied to a specific text I am reading, in order to increase my level of comprehension. While many approach the task of reading in a foreign language by looking up unknown words as they are encountered, I prefer to learn them ahead of time, to avoid the break in concentration while reading. With my bad habit of perfectionism, my main strategy in the past for learning these word has been the “Brick Wall Method”:

The Brick Wall Method – Learn every unknown word you encounter, no matter how difficult or rare it is

My theory has been — like being a brick wall against a tennis player — to not let any unknown word get past me, so that eventually I will run out of unknown words and thus will have learned the language. If a word is used in a text, it’s clearly important to some nominal degree, and if it’s used once, then it’s more likely to be seen again at some point, versus all the words that aren’t in the text.

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A Mathematical Model for Chinese Word Knowledge

The Known Chinese Words Test has been running for a month now. During that time I’ve collected data from 170 trials, from learners with a wide range of levels. The results are very encouraging, so that I can give more details about what I have found. What I have been working on is a mathematical model for word knowledge, which can describe the probability for a particular person to know any word, with just a few variables involved. The results from the collected trials validates that hypothetical model, and I’m elated.

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Word Frequencies from Corpus Data

Knowing the frequency of the Chinese words you are studying helpful in a few different ways. If an unknown word is relatively common, then it’s generally more important to learn that word, compared to a less common word. With that knowledge in hand, you can feel less guilty about removing the rare words from your flashcards, and persist in learning the ones that are common yet difficult. If a word has a low frequency in general, but happens to be used a lot in a particular text, that word may be of interest to study. In the early stages of learning, studying the top N (100, 200, 500, etc.) words as flashcards is an effective way to bootstrap one’s word knowledge before diving into authentic texts. But it’s not 100% effective; the long tail of infrequent words will keep you busy learning new vocabulary for years!

So, how can we obtain word frequency data? With Chinese, it’s trickier than it sounds. › Continue reading…

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