RH: ROBERT's ALMOST-COMPLETE ARCHIVE OF WORKS..... My other blog is "I came, I saw, I solved it" at http://i-came-i-saw-i-solved-it.blogspot.com/.......... Robert Ho REQUEST FOR STATEMENTS at http://roberthorequestforstatements.blogspot.com/2011/01/robert-ho-request-for-statements.html

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Saturday, February 17, 2007

RH: Robert HO's Theory of Brain Language

From: Robert Ho (ho3@pacific.net.sg)
Subject: RH: Robert Ho's Theory of Brain Language
View: Complete Thread (18 articles)

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Newsgroups: soc.culture.singapore
Date: 2003-03-24 07:17:05 PST


The gift of the gab

Why did humans learn to speak languages, while other primates never
got beyond grunting? It's all down to our unique filing system for
words, scientists have found

By Kate Ravolious
24 March 2003


Japanese, English, Swahili and Hungarian might sound completely
unrelated, but it turns out that they have more in common than most of
us realise. Researchers have identified a pattern in all human
languages, and it now appears that this pattern may explain the very
origins of how we began to talk.

How we progressed from being cavemen grunting at each other to
sophisticated social creatures who can discuss anything from making a
fire to Wagner's operas has always been a mystery. What is
particularly strange is that there is no evidence of an intermediate
stage of language; it appears that one morning we tumbled out of our
trees and suddenly started talking. Our closest relatives – animals
such as apes, chimpanzees and gorillas – communicate using a limited
number of signals, with about 30 different signals being the maximum.
All humans speak a language with a massive vocabulary and are able to
convey detailed, precise messages to each other. Why did the other
primates never get beyond the grunting stage – and what made us leap
forward with our language skills?

For a number of years, scientists have recognised that all human
languages follow a pattern, characterised by the frequency of
different words. This is known as Zipf's law, named after the Harvard
linguistic professor George Kingsley Zipf, who died in 1950. Our
speech is peppered with small, ambiguous words (such as "the", "be",
and "to"), but only lightly scattered with longer, more specific words
(such as "elephant", "staircase", "saucepan"). If you were to take all
the words in a book and draw a graph of the number of times each word
appeared, you would draw a steeply dropping curve all the way from the
numerous common words to the "one off" appearances of obscure words.
And, curiously, you would get the same-shaped curve for any text in
any language.

But is Zipf's law just an unusual quirk of language, or does it tell
us something more fundamental? Recently, two physicists decided to
take a different approach to looking at language evolution. Ramon
Ferrer of the Universitat Pompeu Fabra in Barcelona, and Ricard Sole
from the Santa Fe Institute in New Mexico, developed a mathematical
model of how language evolves, and considered how much effort is
required both to speak and listen. When they ran their model, Zipf's
law emerged as a natural consequence of language evolution and proved
to be the most efficient way of communicating. "It shows how the
speaker and listener compromise to be able to communicate," says
Ferrer. Indeed, it begins to shed light on the foundations of human
chatter.

The obvious way to communicate is to create individual signals and
sounds that have one meaning. But this one-to-one language structure
soon runs into problems: after a certain point our brains don't manage
to remember all the different words and what they mean. This
one-to-one method of communicating is where chimpanzees, apes and
gorillas have remained. But at some point in the past, humans
developed a cunning way to remember more words, and this set us on the
path to the language we speak today.

In the same way that it is easier to remember how to bake a cake that
we have baked many times before, it is also easier to recall words
that we have heard many times previously. Knowing that a "zither" is a
type of stringed instrument may come in handy for crossword puzzles,
but it is not common in everyday conversations. So most of us don't
tend to remember the meaning of words such as "zither". On the other
hand, a word such as "the" is incredibly useful for constructing
sentences and crops up frequently in conversation, but it won't score
you many intellectual points if you use it at a dinner party.

Words such as "the" are essential. The more we hear and use a word,
the more likely we are to remember it. Unconsciously, we prioritise
which words we remember. This system – remembering words by their
familiarity – is the most efficient way to memorise them, and explains
why human languages always have a structure that follows Zipf's law.

Ferrer and Sole's model showed that human language lies between two
extreme states. At one end of the scale is a complete lack of
communication where we all make noises but no one understands because
there is no logic to what the sounds mean. And at the other end lies
"perfect communication", where every possible object, action and
feeling has a special word assigned to it. The downside to perfect
communication is that it requires lots of memory and an efficient
indexing system, plus the ability to make lots of different sounds.

Animal languages and artificial computer languages are both at the
"perfect communication" end of the scale. For apes and computers,
every sound they make has an unambiguous meaning. Computers make use
of huge memories to store millions of different words and can
communicate very precise messages. Meanwhile, apes have a limited but
very precise language, which means that they can tell each other they
are hungry, but have difficulty discussing the finer points of the
harmonics in Beethoven's Third Symphony.

Human language teeters between the extremes of nonsense and perfect
clarity, continually balancing the need to communicate with the need
to understand. We sometimes say ambiguous things, but using words with
multiple meanings allows us to construct more sentences and convey a
greater variety of messages than we would otherwise be able to.

So what forced humans into using a Zipf's-law system of remembering
words? "The change from grunting to chattering was quite abrupt,"
Ferrer believes. An environmental change, for example, may have caused
humans suddenly to have a greater need to discuss things. "Because
they didn't have any more memory space for new words they started
using Zipf's law to keep the vocabulary size constant, while still
managing to incorporate more meanings," Ferrer says.

And Zipf's law is not only a clever way to memorise words, it has also
proved to be a useful tool in analysing language. Scientists have been
using Zipf's law to identify plagiarism and to spot authors who write
under pen names.

Just as we all have unique fingerprints, we also all have unique ways
of speaking. Some of us have favourite words we like to use; others
speak in florid sentences; and some just want to make sure that they
are understood. Although everyone's speech and writing obeys Zipf's
law, we all have slightly different wiggles on the graph of our
word-frequency distribution. These nuances of speech are enough to
differentiate one person's speech or writing from another's.

Two Indian scientists used Zipf's law to analyse the works of
Shakespeare. It seems that the Bard was not as prolific a writer as
his canon suggests, and that in fact a number of people wrote under
the name Shakespeare. "When Shakespeare's complete works were
analysed, the word distribution no longer followed Zipf's law," Ferrer
explains. "This is probably due to combining the vocabularies from a
number of different people, and it suggests that there were multiple
authors writing under the name of Shakespeare."

So even Shakespeare can't escape scrutiny. And Zipf's law may yet
uncover more secrets. Authors can no longer guarantee anonymity, and
plagiarism has become easier to spot. Meanwhile, Ferrer's work
confirms that nattering to your neighbour is a truly human
characteristic, and that the tussle between communicating detail and
ease of understanding still goes on.

The compromise is to use a Zipf's law structure that keeps language
finely balanced, like a tightrope walker. At some point, many
thousands of years ago, we tiptoed on to the tightrope and started to
use Zipf's law. Language flourished – and we have been gossiping ever
since.

////////////////////////////////////////////////

RH: WW, your Chinese is almost as good as your English, so you are
better placed to think about this: how does Chinese compare with
English?

I mean that Chinese places enormous strain on our memory because every
single word has to be memorised as an ideogram or Chinese character
instead of being built up from 26 simple letters like English.

Also, how does the grammatical structure of Chinese differ from that of
English? Remember that 'preciseness' is not necessarily 'good' or
indicative of advanced development; it may be that 'flexibility' and
'simplicity' are more important.

Also, spoken Mandarin employs how many? -- 4 main and a few other
tones? This tonal aspect makes it almost impossible for foreigners to
learn it although Chinese seem to be able to learn it reasonably
easily. Does that mean that Chinese brains are more attuned to this
tonal language? Or is it simply a cultural or learned from birth
phenomenon?

Does it require a bigger basic vocabulary in Chinese or English to
communicate passably well?

YP: what does this article suggest to you about designing future
English modules for your students? The balance between a bigger
vocabulary of increasingly 'obscure' words and a smaller vocabulary of
more 'versatile' words that could be better at enabling a wider range
of expression? Between the need of the speaker and the need of the
listener/reader? I have always had a rough rule of thumb about
writing, which is to 'put myself in the shoes of the reader' when I
write so that I can continuously monitor my writing and to know
precisely the effect/meaning I am creating. Does this principle have
any application in your teaching modules?

To end, here is a complete articulation of something on language I
posted in soc.culture.singapore not many weeks ago:

ROBERT HO's THEORY OF BRAIN LANGUAGE

1. Language is the basis of thought.

2. Mathematics is a language, perhaps the most natural language of
the brain.

3. The primary language used by a person is to his brain what the
operating system is to a computer.

4. From (3), some languages are superior to others. Some
characteristics of a powerful language: capable of great sensitivity
and expression like poetry; rigorous enough for philosophical enquiry;
exact enough for the requirements of law; simple to learn yet able to
express complex concepts; and flexible enough to embrace rapid changes
in science and technology.

5. From (2), our brains may be mathematical in construction. For
example, throughout history, there have been numerous 'prodigies' who
could add, subtract, multiply, etc, long strings of multi-digit
numbers instantly. Also, the best chess player in history, Kasparov,
was beaten by Big Blue, a computer. Thus, one of the finest
functionings of the human brain, ie., chess playing, is mathematical.

6. From (2), from the time of Newton, perhaps even earlier, to
Einsten and especially now, mathematics has been and is the sole
language capable of investigating and describing the universe, from
black holes to quantum particles. However, this does not necessarily
mean that the universe is mathematical in nature, it simply means that
our brains are mathematical in nature, which is why we are only able
to explore and describe the universe in terms of mathematics --
aliens, if they exist, with different faculties, may well be able to
explore and describe the same universe in very different terms.

7. From (1), (3) and (4), give your child the best language you can
find, consonant with practical considerations. It may be better for
your child to master one language well than to be merely competent in
two or more languages. It may be better for your child to master one
language first before learning another.

Robert Ho
24 Mar 03
UK


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