Language Log

As we enter the second half of the 15th year since we started Language Log, we've been reflecting on the past and planning for the future.

Yesterday BBC's Radio 4 program "Today", the cultural counterpart of NPR's "Morning Edition", invited into the studio a robot from the University of Sheffield, the Mishalbot, which had been trained to conduct interviews by exposure to the on-air speech of co-presenter Mishal Husain. They let it talk for three minutes with the real Mishal. (video clip here, at least for UK readers; may not be available in the US). Once again I was appalled at the credulity of journalists when confronted with AI. Despite all the evidence that the robot was just parroting Mishalesque phrases, Ms Husain continued with the absurd charade, pretending politely that her robotic alter ego was really conversing. Afterward there was half-serious on-air discussion of the possibility that some day the jobs of the Today program presenters and interviewers might be taken over by robots.

The main thing differentiating the Sheffield robot from Joseph Weizenbaum's ELIZA program of 1966 (apart from a babyish plastic face and movable fingers and eyes, which didn't work well on radio) was that the Mishalbot is voice-driven (with ELIZA you had to type on a terminal). So the main technological development has been in speech recognition engineering. On interaction, the Mishalbot seemed to me to be at sub-ELIZA level. "What do you mean? Can you give an example?" it said repeatedly, at various inappropriate points.

Looking for something else, I stumbled on this unexpected Google Books description of Peter Guralnick's Searching for Robert Johnson:

The first two conditions, along with eight others, are covered in this interesting Sixth Tone article:

"An Awkward, Greasy Year: China’s Top Slang of 2017 " (12/28/17) by Kenrick Davis

Davis's presentation is excellent, so let us begin this post with two montages accompanying his article.

From Paul Sleigh:

From Geoff Dawson:

On display in a current exhibition at the National Library of Australia.

For reasons not strictly relevant to what follows, Yves Schabes and I have been analyzing the novels of Agatha Christie. (For the not-strictly-relevant background, see Xuan Le et al., "Longitudinal detection of dementia through lexical and syntactic changes in writing: a case study of three British novelists", Literary and Linguistic Computing 2011, and Graeme Hirst & Vanessa Feng, "Changes in Style in Authors with Alzheimer's Disease", English Studies 2012.)

It occurred to me to wonder whether the proportion of quoted dialogue might vary from text to text — and since the textual properties of dialogue are likely to be different from those of the narrative voice, this might influence the results of comparisons. So I ran a quick check on seven of Christie's novels, using as proxy the proportion of characters in the novels' texts in spans between quotation marks.

A Shanghainese friend of a friend just sent him a link to a curious video, and he forwarded it to me.  It looks like a Nike-sponsored rap song with five different fāngyán 方言 ("topolects") and lots of English.

My friend asked, "I wonder to what degree the Hànzì 汉字 ("Chinese characters") in the subtitles match the actual lyrics."

The video comes via Bilibili, which sometimes seems to load very slowly.  It is also available on iQIYI and DigitaLing.  Subtitles are more clearly visible in the Bilibili and DigitaLing (last one) versions.

The main questions, at least for me, are which topolects are presented, how faithful the presentations are, and how well the subtitles represent what is being said.

A week ago, I wrote a post on "CCP approved image macros" (12/17/17).  Being the authoritarian, totalitarian government that it is, the Chinese Communist Party (CCP) has the power to coin, sanction, and promote whatever forms of language use it desires.  This week, at the conclusion of 2017, we have this dazzling collection of CCP-approved expressions that encapsulate US-China ties during this year:

"Yearender: 2017 in review: 8 terms that matter in China-U.S. relations" (xinhuanews [12/23/17])

By highlighting these eight terms, the Chinese government clearly wishes us to recall 2017 according to these rubrics and hopes that they will become catchwords.  While I don't think that they will catch on, so to speak, and stick in popular discourse, they do help us understand the mind of the CCP.

This is really strong work from PVD's First Baptist Church. I chuckled when I drove by the sign this evening. Photo credit to their FB page: https://t.co/Ivqmh6QqQ9. pic.twitter.com/4QRJ6PyBSF

— Philip "Read My Book" Eil (@phileil) December 6, 2017

From March through July of 2016, we had a long-running series of posts comparing words in Indo-European and in Old Sinitic (OS),  See especially the first item in this series, and don't miss the comments to all of the posts:

• “Of precious swords and Old Sinitic reconstructions” (3/8/16)
• “Of precious swords and Old Sinitic reconstructions, part 2” (3/12/16)
• “Of precious swords and Old Sinitic reconstructions, part 3” (3/16/16)
• “Of precious swords and Old Sinitic reconstructions, part 4” (3/24/16)
• "Of precious swords and Old Sinitic reconstructions, part 5" (3/28/16)
• "Of shumai and Old Sinitic reconstructions" (7/19/16)
• "Of felt hats, feathers, macaroni, and weasels" (3/13/16)

Today's post is not about a sword per se, but it is about an armament for parrying sword thrusts.  It was inspired by seeing the following entry in Paul Kroll, ed., A Student's Dictionary of Classical and Medieval Chinese (Leiden: Brill, 2015), p. 104a:  fá 瞂  pelta; small shield — Middle Sinitic bjwot.  I asked Paul where he got that beautiful word "pelta", and he replied:  "One of the benefits of my early classical studies. I got it from Vergil, but it’s originally Greek."

Sometimes a new experimental result suggests a very different way of interpreting older results. On a visit a couple of days ago to Ofer Tchernichovski's lab at Hunter College, I encountered a striking example of this effect.

The background is the experimental literature on zebra finch song learning. If one of these birds is raised in acoustic and social isolation, it never learns to sing a species-typical song, but rather continues to produce "proto-song", which is a sort of songbird equivalent of grunts and groans. In contrast, with a relatively brief exposure to an example of adult song during a "critical period" early in life, a bird will (later on) learn to sing properly, in fact imitating the tutor's song quite closely. Crucially, species-typical zebra finch song is made up of discrete "syllables" arranged in regular "motifs", whereas proto-song is relatively diffuse and non-categorical at all time scales.

A decade ago, I reported on some fascinating work from Ofer's lab showing that species-typical song can emerge over a few generations in a colony raised in acoustic isolation, never encountering any external adult models ("Creole birdsong?" 5/9/2008).

Now a newer experiment (Olga Fehér et al., "Statistical learning in songbirds: from self-tutoring to song culture", Phil. Trans. R. Soc. B 2016) adds a result that makes us think differently about the earlier work.

Michelle Goldberg, "Fifty Shades of Orange", NYT 12/22/2017:

At a televised cabinet meeting on Wednesday, Donald Trump, as is his custom, called on his appointees to publicly praise him. In a performance that would have embarrassed the most obsequious lackey of the North Korean leader Kim Jong-un, Vice President Mike Pence delivered an encomium to his boss, who sat across the table with arms folded over his chest, absorbing abasement as his due.

Who was absorbing the abasement, "Vice President Mike Pence" or "his boss"?