Language Log

To access an article in the Financial Times yesterday I found myself confronted with a short market-research survey about laptops, tablets, and smartphones. Answer three our four layers of click-the-box questions, and I could get free access to the article I wanted to look at. A reasonable bargain: clearly some company was prepared to pay the FT for access to its online readers' opinions. And at the fourth layer down I faced a question which asked me to choose a single word that comes into my mind when I think of a certain Microsoft product.

My choice, from all the tens of thousands of words at my disposal, and the word I picked would go straight into the market research department of the one corporation, above all others, for whose products I have the greatest degree of contempt. Just choose that one evocative word and type it in, and I would be through to my article. A free choice. Which word to pick?

Let me explain, very informally, what a predictive text imitator is. It is a computer program that takes as input a passage of training text and produces as output a new text that is composed quasi-randomly except that it matches the training text with regard to the frequencies of word or character sequences up to some fixed finite length k.

(There has to be such a length limit, of course: the only text in which the word sequence of Melville's Moby-Dick is matched perfectly is Melville's Moby-Dick, but what a predictive text imitator trained on Moby-Dick would do is to produce quasi-random fake-Moby-Dickish gibberish in which each sequence of not more than k units matches Moby-Dick with respect to the transition probabilities between adjacent units.)

I tell you this because a couple of months ago Jamie Brew made a predictive text imitator and trained it on my least favorite book in the world, William Strunk's The Elements of Style (1918). He then set it to work writing the first ten sections of a new quasi-randomly generated book. You can see the results here. The first point at which I broke down and laughed till there were tears in my eyes was at the section heading 'The Possessive Jesus of Composition and Publication'. But there were other such points too. Take a look at it. And trust me: following the advice in Jamie Brew's version of the book won't do your writing much more harm than following the original.

[This is a guest post by Nathan Hopson]

NHK reported yesterday on the recently released results of the Agency for Cultural Affairs' annual survey of the changing uses of Japanese. This year, the survey of 3500 men and women 16 and up received responses from 54%. The most interesting results reflected the impact of online and SMS language use by young people.

Adam Rosenthal told me in an email recently:

While trying to enter my address into American Airlines' horribly designed phone app, I was asked to wait, because "States/Provinces are still populating for the first time".

What the hell was going on? I'm sure you regular readers will be able to guess.

A phishing spam I received today from "Europe Trade" (it claims to be in Wisconsin but its address domain is in Belarus) said this:

Good Day sir/madam,

I am forwarding the attached document to you as instructed for confirmation,

Please kindly do the needful and revert

Best regards
Sarah Griffith

There were two attachments, allegedly called "BL-document.pdf" and "Invoice.pdf"; they were identical. Their icons said they were PDF files of size 21KB (everyone trusts PDF), but viewing them in Outlook caused Word Online to open them, whereupon they claimed to be password-protected PDF files of a different size, 635KB. However, the link I was supposed to click to open them actually led to a misleadingly named HTML file, which doubtless would have sucked me down to hell or sent all my savings to Belarus or whatever. I don't know what you would have done (some folks are more gullible than others), but I decided I would not kindly do the needful, or even revert. Sorry, Sarah.

In "Voice recognition for English and Mandarin typing " (8/24/16), we took a brief look at a Stanford-University of Washington-Baidu study that showed, according to an NPR article, that voice recognition finally beat humans at typing.  The title of the original study is "Speech Is 3x Faster than Typing for English and Mandarin Text Entry on Mobile Devices", and the authors are Sherry Ruan, Jacob O. Wobbrock, Kenny Liou, Andrew Ng, and James Landay.

A rather poetic and imaginative abstract I received in my email this morning (it's about a talk on computational aids for composers), contains the following sentence:

We will metaphorically drop in on Wolfgang composing at home in the morning, at an orchestra rehearsal in the afternoon, and find him unwinding in the evening playing a spot of the new game Piano Hero which is (in my fictional narrative) all the rage in the Viennese coffee shops.

There's nothing wrong with the sentence. What makes me bring it to your notice is the extraordinary modification that my Microsoft mail system performed on it. I wonder if you can see the part of the message that it felt it should mess with, in a vain and unwanted effort at helping me do my job more efficiently?

In all tech considered (8/24/16), Arrti Shahani has an article titled "Voice Recognition Software Finally Beats Humans At Typing, Study Finds".

Turns out voice recognition software has improved to the point where it is significantly faster and more accurate at producing text on a mobile device than we are at typing on its keyboard. That's according to a new study by Stanford University, the University of Washington and Baidu, the Chinese Internet giant. The study ran tests in English and Mandarin Chinese.

Baidu chief scientist Andrew Ng says this should not feel like defeat. "Humanity was never designed to communicate by using our fingers to poke at a tiny little keyboard on a mobile phone. Speech has always been a much more natural way for humans to communicate with each other," he says.

There are so many people out there designing apps.  It's potentially a very lucrative business, since, if you come up with the right app to fill a need for millions of people, you can strike it rich.  Consequently, with thousands of people coming up with new apps all the time, there seems to be an app for almost everything under the sun (but not quite — so there's still plenty of room for the designers to come up with more seemingly specialized apps, yet nonetheless fulfilling somebody's requirements).

Christina Xu has written "A Field Guide to China's Most Indispensible Meme" (Motherboard, 8/1/16).  Her essay includes more than a dozen illustrations, the first of which is this one:

I was recently moved (screaming and struggling, as four strong men held me down by my arms and legs) to a new web-based university email system designed and run by Microsoft: Office 365. Naturally, it's ill-designed slow-loading crap, burdened by misfeatures and pointless pop-ups that I do not want popping up, and it fails to allow various elementary operations that I often need (every upgrade is a downgrade). But that is not my topic today. I want to note one special sad consequence of moving to an entirely new system: all my previous email system's Bayesian machine learning about spam classification has been lost. The Office 365 system has had hardly any data to learn from as yet, so I am seeing some of the stuff that would have been coming to me all along if it had not been caught by machine learning and dumped in the spam bin. And what has truly amazed me is the daily flow of advertising for spamferences and junk journals.

It began with a one page think piece by Ted Chiang in the New Yorker (5/16/16) that we describe and discuss here:

"Ted Chiang uninvents Chinese characters" (5/13/16)

 This is a guest post by David Moser of Beijing Capital Normal University

For those of us who teach and research the Chinese language, it is often difficult to describe how the Chinese characters function in conveying meaning and sound, and it’s always a particular challenge to explain how the writing system differs from the alphabetic systems we are more familiar with. The issues are complex and multi-layered, and have important implications for basic literacy and the teaching of Chinese to both native speakers and foreign learners. Tom Mullaney, a professor of history at Stanford University, has lately been muddying these pedagogical waters in a series of articles and interviews that seriously misrepresent the merits and relative advantages of the alphabet over the Chinese script.