Blog » Readability Code Open Sourced
In July 2004 I wrote some code to calculate the readability of text using the most common algorithms available (Flesch-Kincaid and Gunning-Fog). The code hasn't aged well, and had many flaws, especially when it came to the subject of syllable counting.
Syllable counting is a tricky prospect. Consider the following sentence, for example: "I moped about, hopeful that my moped would be back on the highway soon". Sound innocuous? There's a pair of homographs in there (two words, spelled the same, that sound different) - and these have different syllable counts depending on which of the two words you mean. Words can be almost identical, with the same order and number of consonants and vowels (and it's that order you generally use to calculate syllable numbers) - "sired" has one syllable, while "sided" has two. Throw in prefixes, suffixes, plurals and compound words and you've got yourself a challenge.
Syllable counting is a minefield, with a small set of rules and a massive set of exceptions to handle.
That said, I've spent some time working through a set of test data and have come up with a small set of rules to take on the task. It helped tremendously having the work of Greg Fast (creator of Perl module Lingua::EN::Syllables) handy for reference, and setting up a decent set of unit tests allowed me to experiement with different rules until I found a set that works. So far. I expect to find more and more exceptions as time goes on, and hopefully the rules can be expanded to account for them.
It wasn't just the syllable counting that was bad. The code was inefficient, disorganised, and incapable of handling anything unpredictable (every extra space counted as an extra word, for example). There were lines in there that didn't make any sense. And I hadn't documented anything, so couldn't tell you why I'd added them in the first place. Oh to be that young and inexperienced again ...
So, as with the other releases in the last few weeks, I went back and rewrote the code properly. The new and improved version has been released as a Google Code project by the name of PHP Text Statistics. It's released (as with the other projects I've set free recently) under a New BSD License.
It consists (so far) of a single class that will tell you various things about the text you feed it:
- String length
- Letter count
- Syllable count
- Sentence count
- Average words per sentence
- Average syllables per word
It will also calculate the readability of the text you enter according to the 6 known algorithms (links go to Wikipedia):
- Flesch Kincaid Reading Ease
- Flesch Kincaid Grade Level
- Gunning Fog Score
- Coleman-Liau Index
- SMOG Index
- Automated Reability Index
There is also a PHP4 compatible version of the code. At the time of writing, it returns the correct scores for test data, though given PHP4's decline and the rise of PHP5, this version may not remain as current as the previous file.
Next thing to be aware of is the unit tests included in the project. There's no easy way to check your calculations are correct, unless you have a set of verified numbers to compare them against. So, I put together (so far) three files with a variety of different tests for the code. These tests should be run with PHPUnit and at the time of writing they all pass (which means there's not enough of them yet).
The basic unit test class lists a large selection of words and compares their calculated syllable count with their actual syllable count (worked out the old fashioned way). It includes a variety of tests to ensure sentence counting and word counting both work as intended. It also includes a small selection of sentences, for which readability scores have been calculated by hand, and checks that the class returns the correct scores for these items.
Rudyard Kipling's If is, aside from a brilliant piece of inspiring poetry, one long sentence comprised of lots and lots of short words (take a look - impressive how few of the words are multi-syllabic). This file contains a selection of tests to run against If. It checks all of the words of the poem have their syllable count correctly calculated, and that all of the readability scores are correctly calculated, by matching the calculated scores against hand-calculated numbers.
Herman Melville's Moby Dick is up next (well, the first paragraph is - I'm not prepared to count, by hand, the number of syllables in the entire book). Like If, it is (I believe) in the public domain, so can be used for this sort of purpose without complications. It's also a brilliant read. This file contains a selection of tests to run against the first paragraph of Moby Dick. It checks all of the words of the passage have their syllable count correctly calculated, and that all of the readability scores are correctly calculated, by matching the calculated scores against hand-calculated numbers.
This project can benefit from the involvement of people in many ways. Initially, the most helpful thing anyone can do is find words whose syllable count is not correctly calculated by the script and add a new test for that word. There are going to be a lot out there (especially compound words, like "shoreline", and odd words that are not pronounced according to normal rules, like "simile").
The class could be expanded to give more information about text - like letter frequencies, word and phrase freqencies (useful for SEO) and unique word count, among other things. I've made a start on making the code multi-byte character set safe, but there's lots more to do there too.
The really brave could add more test text, too. Paragraphs of (public domain) text provide an excellent way to check the tool is working as it should. I'd suggest using either the Kipling or Melville file as a template to work from, and prepare for a boring few hours. You get a great feeling of satisfaction at the end, though, when the whole thing is done!
There's a discussion group for ... well, discussion. Suggestions, comments and feedback all welcome. If you would like to get involved in this project, start there (or email me), or grab a copy of the code from the SVN repository on Google Code.