Language Log

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.

This is a topic that we have frequently broached on Language Log:

• "Character Amnesia" (7/22/10)
• "Character amnesia revisited" (12/13/12)
• "Spelling bees and character amnesia" (8/7/13)
• "Character amnesia and the emergence of digraphia" (9/25/13)
• "Dumpling ingredients and character amnesia" (10/18/14)
• "Character amnesia in 1793-1794" (4/24/14)
• "Japanese survey on forgetting how to write kanji" (9/24/12)

In several recent messages to me, Guy Almog has raised the issue once again.  This is not unexpected for someone whose ongoing research focuses on the changing writing and reading habits of native Chinese and Japanese speakers, and mainly with issues of memory and forgetfulness of hanzi / kanji.

Success: Xiaoice is a Microsoft chatbot program that has become popular in China.  Her name is written in various ways:

"Xiaoice" 42,400 ghits (that's pronounced "xiǎo ice")
"小冰" 362,000 ghits (that's pronounced "xiǎo bīng")
"小ice" 11,200 ghits (that's pronounced "xiǎo ice")
"Little Bing" 16,000 ghits (she's obviously named after Microsoft's search engine*)
"Little Ice" for the chatbot doesn't work, because that's the name of Ice-T's son.

Not all of these ghits are to the Chinese chatbot program; some are for Facebook and Twitter monikers, etc., but most do refer to the Microsoft chatbot.

Mark Metcalf writes:

Since Language Log addresses lots of interesting language-related issues, I was wondering if you'd ever encountered a problem with Chinese PDFs being incorrectly displayed on an iPad. I searched the LL website and didn't find it previously addressed. I also unsuccessfully searched the Web for solutions.

Here's the issue: Last week I downloaded several articles from CNKI and they all display correctly on my Windows machine. However, when I transferred them to an iPad the Chinese text was garbled. Since I haven't had iPad problems with Chinese PDFs from other sources, one thought is is that CNKI uses a modified PDF file format that can't be properly handled by the iPad OS.

Has anyone previously addressed this problem? If so, could you point me to a solution? If not, would you be interested in addressing this on 'Language Log'? Below I've attached before/after versions of the displays.

I asked several colleagues and students whom I've often observed reading Chinese PDFs on their iPads what their experience with CNKI has been.  Here are a few of the replies that I received.

In "Kongish" (8/6/15), we looked at the phenomenon of extensive mixing of English and Cantonese by young people in Hong Kong.  We also became acquainted with the Kongish Daily, a Facebook page written in and about Kongish.  Many Language Log readers thought it was a satire or parody and that it was an ephemeral fad that would swiftly fade away. But here we are, half a year later, and the movement is still going strong, and even, it would seem, gaining momentum.

On the otoro blog, there is another amazing article about sinograms:

"Recurrent Net Dreams Up Fake Chinese Characters in Vector Format with TensorFlow" (12/28/15)

I say "another amazing article" because, just a week ago, in "Character building is costly and time consuming" (12/22/15), we looked at a fascinating report on the vast amount of labor necessary to build fonts made up of real Chinese characters.  Basically, the latter report examined the history of Chinese characters and then explained how typographers create new fonts comprising all the characters necessary for printing books, newspapers, magazines, advertising copy, and so forth.