Language Log

Given this:

"Measure words for robots" (9/4/21)

and this:

"Arigatō" (9/3/21),

I could not help but think of this:

Christian Horn was reading an article in Japanese Endgadget (8/11/21) about the introduction of a new kind of robot called a "Cyberdog".

Says Christian:

You don't need to know Japanese to understand the fascinating part:  in Japanese, when counting things, the type of "thing" you are counting is relevant.  So you count "flat things" differently than "long shaped" things.  Or machines, fish, or animals.

The article states that Cyberdog is aimed at developers, and is limited to "1000台(匹?)", showing hesitation over which measure word to use, dai 台 (counter for machines, including vehicles) or hiki 匹 (counter for small animals​; counter for rolls of cloth; counter for horses​).  If you use dai 台 as a measure word for counting Cyberdogs, it would indicate that you think of them as machines.  If you use hiki 匹 for counting them, it would indicate that you regard Cyberdogs as animals.

Article by Holly Else in Nature (8/5/21):

"‘Tortured phrases’ give away fabricated research papers

Analysis reveals that strange turns of phrase may indicate foul play in science"

Here are the beginning and a few other selected portions of the article:

In April 2021, a series of strange phrases in journal articles piqued the interest of a group of computer scientists. The researchers could not understand why researchers would use the terms ‘counterfeit consciousness’, ‘profound neural organization’ and ‘colossal information’ in place of the more widely recognized terms ‘artificial intelligence’, ‘deep neural network’ and ‘big data’.

Further investigation revealed that these strange terms — which they dub “tortured phrases” — are probably the result of automated translation or software that attempts to disguise plagiarism. And they seem to be rife in computer-science papers.

Research-integrity sleuths say that Cabanac* and his colleagues have uncovered a new type of fabricated research paper, and that their work, posted in a preprint on arXiv on 12 July¹, might expose only the tip of the iceberg when it comes to the literature affected.

[*VHM:  Guillaume Cabanac, a computer scientist at the University of Toulouse, France]

I've written several posts about unpredictable typing mistakes that are not the result of auto-correct or sloppiness, but are produced through phonological confusion in my own neuro-muscular hardware and software (see "Selected readings").  This morning I experienced another funny occurrence of such a mistake.

I had lost over 7,000 of the recent e-mails in my inbox, so I wrote to the excellent IT guys in Williams Hall:

Crisis

I'm making good progress moving things from inbox to archives, but I just had a disaster.  Everything in my inbox between these two e-mails is missing:

Margaret ********   today (6/18/21) 11:53 a.m.

MISSING

Jing ***  (11/18/20)  11:06 p.m.

There are thousands of important e-mails to me with all sorts of information, attachments, and so forth that I need to take care of, some of them very soon.

Can you somehow restore the missing items?

Have you tried the Google Translate app on your phone? It has a camera tool that automatically translates text that you point it to, but it looks like it needs some work for Mandarin…

I tried to translate a bag of chinese rice crackers using google translate and these are some of the ingredients it gave me pic.twitter.com/cWIghhrWOs

— Claire!!!!!!! (@awkwardfoxes) February 10, 2021

This has been making the rounds:

1. Go to Google Translate.
2. Set the input language to Spanish.
3. Paste in "soy milk"
4. Set the output language to English or X language.
5. Hilarity ensues.

The obligatory screen shot:

Sensational article by Hagar Hosny in Al-Monitor (7/23/20):

"Google presents new tool to decode hieroglyphics:  Google has created a new tool to translate hieroglyphics into English and Arabic at the stroke of a key."

It starts like this:

In a July 15 press release, Google announced the launch of a new tool that uses artificial intelligence to decipher Egyptian hieroglyphs and translate them into Arabic and English.

Google said that the tool, dubbed Fabricius, provides an interactive experience for people from all over the world to learn about hieroglyphics, in addition to supporting and facilitating the efforts of Egyptologists and raising awareness about the history and heritage of ancient Egyptian civilization.

“We are very excited to be launching this new tool that can make it easier to access and learn about the rich culture of ancient Egypt. For over a decade, Google has been capturing imagery of cultural and historical landmarks across the region,” Chance Coughenour, program manager at Google Arts and Culture, said in the statement.

From an anonymous correspondent:

An amusing translation glitch: Google translates the Japanese word "migaku 磨く" (to polish, to brush) to the French word "polonais" (Polish, as in "of Poland").

The full translation party: "migaku 磨く" → "polonais" → "kenma 研磨" (polishing, grinding) → "polissage" (proper French for polishing).

Unfortunately, most customer service chatbots are not nearly this good:

Customer Service Calls pic.twitter.com/CbU67Hpfts

— Jeff Wright (@JeffRightNoww) May 19, 2020

[This is a guest post by Cyrus Shaoul]

I am a long time LL reader and I came across an interesting machine translation error today.

When my Japanese friend sent me this sentence:

62年前のこの日に慶應義塾大学病院で命を授かりました。

I was flummoxed by the verb 授かる [VHM:  sazukaru {"be gifted / endowed with (an award / title); to be blessed (e.g., with a child); be granted / taught; to be given something of great value / a treasure, by deities or someone of higher social class"}] at the end of the sentence, so I asked Google Translate for help and lo and behold, it said:

"On this day, 62 years ago, I died at Keio University Hospital."

This period of prudent isolation is a good time to remember that linguistic analysis applies not only to sound, structure, and sense, but also to social interaction. As the first in a series of posts on this topic, we feature Eve Armstrong's brilliant application of simulated annealing to a problem currently on hold, but sure to re-emerge in full force when our lives de-virtualize: "An Artificially-intelligent Means to Escape Discreetly from the Departmental Holiday Party; guide for the socially awkward" (4/1/2020)G:

We shall employ simulated annealing to identify the global solution of a dynamical model, to make a favorable impression upon colleagues at the departmental holiday party and then exit undetected as soon as possible. The procedure, “Gradual Freeze-out of an Optimal Estimation via Optimization of Parameter Quantification” – GFOOEOPQ, is designed for the socially awkward. The socially awkward among us possess little instinct for pulling off such a maneuver, and may benefit from a machine that can learn to do it for us.

A few months ago, I posted about a talk I gave at an Alzheimer's Association workshop on "Digital Biomarkers".

Overall I told a hopeful story, about the prospects for a future in which a few minutes of interaction each month, with an app on a smartphone or tablet, will give effective longitudinal tracking of neurocognitive health. […]

Speech-based tasks have been part of standard neuropsychological test batteries for many decades, because speaking engages many psychological and neurological systems, offering many (sometimes subtle) clues about what might be going wrong.

But I emphasized the fact that we're not there yet, and that some serious research and development problems stand in the way. […]

Some colleagues and I are starting a large-scale project to get speech data of this general kind: picture descriptions, "fluency" tests (e.g. "how many words starting with F can you think of in 60 seconds?"), and so on. The idea is to support research on analysis of such recordings, automated and otherwise, and to allow psychometric norming of both traditional and innovative measures, for both one-time and longitudinal administration, across a diverse population of subjects. We've got IRB approval to publish the recordings, the transcripts, and basic speaker metadata (age, gender, language background, years of education).

We've been testing the (browser-based) app across a variety of devices and users. When it's ready for prime time, this is one of many channels that we'll use to recruit participants — we're hoping for a few tens of thousands of volunteers.

We're finally ready to open this app to wider use, and you can contribute a few socially-distant minutes of your time by going to https://speechbiomarkers.org. And please tell your friends!

[This is a guest post by Nathan Hopson, who sent along the two screen shots with which it begins.]

Another splendid example of why punctuation matters and why machine translation is dumb…