D. The arbitrariness of human language
A less definable characteristic of human language is its arbitrariness, which takes several forms. First there is no necessary connection between the object and the word that represents it. A rose could be called a sorp and smell as sweet. Different languages indeed call the same object by different names. English rose may indeed be rose in French but it is bara in Japanese and warda in Arabic. The connection between objects and words is largely arbitrary.
Language is also arbitrary in that it relies on
combinations of a small set of sounds or shapes that do not have meaning in
themselves. The sounds / b / , / 
/ , / g / have no meaning separately; the question
‘What’s an / /?’ cannot be answered by explaining what / / means.
Only when / / is combined with the other sounds of English to get /bg/ (bog)
or /gb/ (gob) does the sound become
meaningful. Phonemes and letters do not have meaning but they combine to form
words that do, as seen in Chapters Three and Five.
Animal languages in a sense have a limited list of ‘words’, like those Konrad Lorenz found in crows. In animal communication, a ‘word’ is an entity of its own. Each of the monkeys’ cries has a distinctive meaning, ‘snake’, ‘eagle’, and so on. They cannot be decomposed into a small set of meaningless components like phonemes. Animals have a dictionary consisting of a limited number of signs but they do not have sound or writing systems.
In human languages the set of words is open-ended, formed from a strictly limited set of components, whether phonemes, gestures, or letters. The fact that these symbols are themselves meaningless and arbitrary allows them to generate a vast stock of words. Though Roman alphabets vary slightly from one language to another, their 26 letters can encode, not only all the words in the Oxford English Dictionary, say, but all the words in the dictionaries of French, Italian, Malaysian, etc, as well, with a handful of additional symbols. Arbitrariness of the actual phonemes or letters is a highly useful characteristic that gives language its infinite flexibility, unlike the total rigidity of animal systems
III. Teaching monkeys human language
In their natural habitat, animals show few signs of the kind of communication system that makes up human language. The potential for language could nevertheless be latent inside them, waiting to be revealed. A number of experiments in the last thirty years have attempted to establish whether a human language can be taught to another species. The assumption is that the problems apes have with human speech come from their different physiology and vowel ‘space’, rather than from mental incapacity for language. If apes were taught a human language that did not involve speech, their ability to learn language could be tested independently of their problems with producing and hearing speech sounds.
Apes and visual language
One
approach was to invent a new visual language called Yerkish that could be taught
to apes. The apes communicated with a human being via a computer keyboard. When
the ape touched a key, a ‘lexigram’ was displayed on a screen above. Lexigrams
consisted of simple geometric signs similar to crude characters: for example 
stood for ‘dessert’
and 
for ‘coconut’.
The answers to the ape came from a human being sitting in another room, partly through signs on the screen, but also through tickling, the provision of sweets, and so on. A typical example is an ape called Sherman requesting ‘Want orange drink’ on the keyboard; when he got the drink, he typed ‘Pour orange drink’; later, to get a drink out of his reach, he requested ‘Give straw’. By typing in the right symbols, the monkey could thus get food, drink, or even films, as well as attention from human beings. Yerkish functioned as a communication system where information was transferred from ape to human. Yerkish furthermore was arbitrary in that the symbols consisted of combinations of nine abstract shapes. A sentence in Yerkish could be up to seven symbols long.
The first chimp to be taught by this system, called Lana, succeeded in producing strings of Yerkish symbols, such as ‘Please Tim give apple’ or ‘Question you give coke to Lana in cup’. She could also put together new combinations of lexigrams for objects for which there was no word in her vocabulary. When she wanted an orange, for example, she produced the signs ‘Question Tim give apple which-is orange’.
Still more remarkable is the pigmy chimpanzee called Kanzi. Kanzi’s mother was taught Yerkish in the usual way, accompanied by her son, who appeared to take little interest in what was going on. But, when she left the project temporarily, Kanzi suddenly showed that he had picked up Yerkish simply by observing his mother being taught. By the age of five years, he was handling about 150 ‘words’; at six he could respond successfully to around 300 different ‘sentences’ in natural settings, using a transportable board with Yerkish symbols. One successful routine involved Kanzi naming any one of seventeen locations in the surrounding estate, such as ‘tree-house’, and then taking the human being there, with 100% accuracy. Clearly Kanzi was able to comprehend certain aspects of communication, although much of his conversation was only concerned with food.
Apes and sign language
Sign language is another way of circumventing the problems of producing speech from non-human speech organs. Human sign languages have fully developed gesture systems rather similar to those of speech, as mentioned in Chapter Three. While some of the gestures of human sign languages resemble ‘natural’ gestures like those of the wild chimp, most are as stylised and arbitrary as any of the sounds of speech, just as the origins of the letter "A" as the shape of an ox’s horns are now less than obvious. The British Sign Language gesture of pointing at someone with the right hand clenched and first finger extended may well be readily interpreted as ‘you’, but it is far from obvious that the first finger of the right hand stroking down the right cheek from ear to chin means ‘woman’. Hence there is no more a universal world sign language than a universal spoken language, with large differences between American Sign Language, British Sign Language, Chinese Sign Language, and so on.
A gorilla called Koko was taught American Sign Language (ASL) and spoken English simultaneously from one year of age; a sentence in ASL was used at the same time as a spoken English equivalent. Initially she was taught ASL for five hours a day, partly by imitating signs, partly by moving her hands in the appropriate ways. Then she was put in an environment where ASL was used for about ten hours a day by a variety of human companions. By the age of 5½, she had mastered 246 signs of ASL, such as ‘alligator’, ‘cake’, ‘small’, and ‘pour’. More importantly, she had started to put these separate signs together into two-word combinations such as ‘Food-more’, ‘Me-up-hurry’, and ‘No-gorilla’, many of which she could not have received from her human companions. A toy zebra was called a ‘white tiger’, a cigarette lighter a ‘bottle match’ and a mask a ‘face hat’. These sentences have an uncanny resemblance to the two-word sentences like mommy sock found in children’s early speech, as discussed in Chapter Seven.
Can apes be taught language?
At first sight these experiments, and the several others that were performed, are impressive. Apes do seem capable of acquiring a rudimentary human communication system together with a reasonable number of words. They also use a definite word order. Koko for instance used adjective–noun order 75% of the time, as in ‘dirty mouth’, ‘dirty taste’ and ‘old wrong grass’. Moreover the apes are capable of producing new ‘sentences’ such as ‘cookie rock’ when required – the creativity previously attributed only to human beings.
Yet linguists have reacted to these experiments with extreme scepticism. For instance one danger is reading things into the apes’ language which are not actually there. It is all very well to claim that Lana said ‘Question Tim give apple which-is orange’. What actually happened is that she tapped a series of buttons that produced six symbols on a screen. What she ‘meant’ by them is unknown. Yet, to give her credit, a human being might find a computer that talked back to them fairly confusing. Yerkish was hardly communicating directly with a visible listener in a concrete interaction like most human language.
The signs that the apes produced were analysed as if they were ASL. Some, however, may have been versions of the ape’s natural signs. A chimp called Washoe for example used the natural ‘hurry-up’ and ‘give me’ signs. But her natural gesture for ‘give’ was interpreted by observers as an ASL sign. Her spontaneous gesture of putting the arms up to be tickled was interpreted as the ASL sign for ‘more’. However, in both cases they lacked crucial features of the ASL sign. Hence much of the apes’ apparent signing ability in ASL is little more than their natural gesture system, lacking the arbitrary nature of a true sign language.
More crucially, ASL has meaningless components that combine to make words, in the usual human fashion. The ASL signs for ‘summer’ and ‘ugly’ use the same handshapes and movement but differ in where they are produced. Like the difference in tongue contact between /t/ and /d/, it is a matter of articulation. A single ASL sign is made up of several components. ASL does not consist of natural gestures but is a systematic system of arbitrary signs, even if the natural origins of some signs are transparent. The chimps, however, treated each sign as a whole, not as having separate components. In particular they did not see any significance to the place where the sign was made, for example on the shoulder versus on the stomach, but used it anywhere on the body, a similar ‘mistake’, say, to treating /k/ as /t/.
So it is debatable whether the apes were showing any capacity for language other than the ability to acquire a certain number of signs and to put some of them in a sequence. Chapter Two saw how human language has phrase structure; the sentence is formed out of interlocking phrases; it is not just words in order. At best the apes had a linear sequence of signs. Kanzi was also only 75% correct on adjective–noun order. A human child rarely makes a mistake with the position of adjectives at any stage of language acquisition; book blue for blue book is highly unlikely (apart from the fact that in child English the verb is can be missing, i.e. book blue meaning ‘the book is blue’ rather than ‘the blue book’).
There are then considerable doubts whether the apes’ communication was truly language-like. However, to some extent the goal-posts have been shifted. Apes can undoubtedly be taught to communicate information through a language system of a sort. The slightly different claim now is that the type of system they employ does not resemble a human language. The upshot is that it still has not been proved that a human language can be taught to another species. While the conditions for the acquisition of language in these experiments were ideal, it did not take place convincingly. The missing factor is the inherent structure of the human mind, to be elaborated below. To be fair, it should be pointed out that several of the case studies such as Kanzi and Koko are actually ‘bilingual’ acquisition of two human languages, ASL and English, rather than ‘monolingual’ acquisition of a single language. While human children have no problems in acquiring more than one language in early childhood, apes may find it more confusing to acquire two languages at once.
Even compared with a young human child, the apes did not begin to tap the complexity of human language. Furthermore, apart perhaps from Kanzi, apes had to be taught language, as Chomsky has often argued; they did not pick it up from their parents as described in Chapter Seven. Even if apes have been taught a human language successfully, this does not explain why language has not spontaneously arisen in the wild if the capacity is latent in their minds. It would be strange for it to be latent without them ever actually using it. But the features of our own human language may of course blind us to the languages of animals.
An interesting counter-experiment is to see whether the languages taught to apes could be taught to human beings who have failed to learn language successfully. What happens if you teach language-deficient children a simple visual language like Yerkish? Four such children were trained for nine weeks to use Yerkish with plastic shapes. The children were able to express ideas such as ‘give’ and ‘take’, negatives, and questions, so they had in effect acquired the same type of system as the apes. If children who are relatively unsuccessful at learning human language can learn such systems with ease, they are evidently not the same as ordinary human language.
However, the same argument about chimps not being able to speak could be given in reverse. These human children are capable of making human speech sounds, so the experiment may have overlooked the ease of sounds to human beings. This loophole was filled by an experiment with a computer system which substituted sounds for shapes. The four children tested learnt at least six ‘nouns’ and four ‘verbs’. After nine sessions, one child could produce two- and three- element ‘sentences’ such as ‘Give doll’ and even some four-element ‘sentences’ such as "Doll give monkey to-cat". Sounds were not the crucial element since the children could manage without them.
To sum up this section, teaching language to apes has met with limited and controversial success. The parts of language that apes acquire do not seem to be those that are most crucial to human language. Language appears to be unique to the human species, at least in the form that we know it.
A Day in the Life of a Chimp
Here is a selection of the Yerkish sentences produced by Sherman, a 4½ year-old chimp, on one day, given in order of frequency.
Out room Pour orange drink Austin [another chimp] Open Sue [a researcher] M&M [a sweet] Give Columbus Stick Columbus Room out Outdoors Gone Wrench Room Give out room Money Milk Magnet Give Sherman M&M Sherman out room Want orange drink Give open Tickle Door Sherman give M&M Sherman M&M Sherman room out Give pudding Scare Sweet potato Give pour drink Slide Door Austin Yes Sue Go outdoors Orange drink Sponge Juice Blanket Key No Give money Give milk Yessource: Savage-Rumbaugh and Rumbaugh, 1980
It is hard to decide whether the resemblances between these and the two-word utterances of children seen in Chapter Seven are accidental or show a similar knowledge of language .
IV. Computers and language
The question of whether computers can think has been raised ever since they were first invented. The problem is deciding when a computer is doing something that would be called thinking in a human being. Alan Turing proposed a classic way of testing this problem, called the ‘Turing test’. Suppose a person sits in a room with only a computer terminal for company, rather like Sherman. The person has to communicate with two other people through the keyboard; one of the people is a human being sitting at another terminal, the other is the computer program itself. If the person can tell whether a person or a machine is ‘communicating’, the computer has failed the test. But, if the computer cannot be distinguished from the real person, it passes the test. In other words, if the behaviour of a computer cannot be distinguished from that of a thinking person, it must be credited with thinking just we credit our friends and relations with thinking. If it smells like a Boojum, tastes like a Boojum, and looks like a Boojum, there is not much point in denying it is a Boojum. The question has shifted from thinking to language: if a computer can use language in the same way as a human being then it must be able to think.
Of course a computer could easily be distinguished from a person by its superior ability to carry out complex activities. Ask it the square root of 34.7879 and it produces 5.897372296201 in a split second: a human using pen and paper would come in many minutes later. But this answer is a matter of rote calculation, not thinking. Language provides a better test-case than mathematics. If a person cannot tell a computer’s language from that of a human being, the computer is in effect using language in the same way as a human being: in which case, language would no longer be unique to human beings.
Joseph Weizenbaum devised a program called ELIZA to take the Turing test. He started by making the same concession to the computer as to the ape by letting it bypass the actual sounds of speech and communicate in writing. Here is an short extract from an ELIZA session at a computer keyboard in which a ‘patient’ is communicating with a computer-simulated psychiatrist. As always, the convention is that the computer talks in capital letters.
Men are all alike.
IN WHAT WAY.
They’re always bugging us about something or other.
CAN YOU THINK OF A SPECIFIC EXAMPLE.
Well my boyfriend made me come here.
YOUR BOYFRIEND MADE YOU COME HERE.
He says I’m depressed much of the time.
I AM SORRY TO HEAR YOU ARE DEPRESSED.
It’s true I am unhappy.
DO you think coming here will help you not to be unhappy?
I need some help, that much seems certain.
What would it mean to you if you got some help?
Perhaps I could learn to get along with my mother
Tell me more about your family. ....
Apparently the computer is responding intelligently to whatever the person types in. It comments on feelings, I AM SORRY TO HEAR YOU ARE DEPRESSED; it asks for elaboration, Tell me more about your family. It asks for reasons, DO you think coming herE WILL help you not to be unhappy? In other words it seems to be fully engaged in the conversation, like a human being. People who have used this program felt the strong illusion that the computer was understanding them; Weizenbaum’s secretary would ask him to leave the room so that she could converse with it in private. The users often then treated the computer as if it were a human being and thus it in effect passed the Turing test.
The actual computer program, however, gives the game away. For the computer is only looking for strings of letters in the input which match those in its word-list; when it finds a match, it produces another pre-set string. So it is programmed to look for the six letter string mother. When it finds it, the computer produces the predetermined string Tell me more about your family. It will do exactly the same if it finds I hate my mother, I love my mother, the mother of wars, Mothering Sunday or, probably, He smothered it with attention. There is no sense in which it knows that mother is a word with a meaning; all it possesses is a match between a string of letters and another, which might as well be §¢Ð, and âå µµÒ¾‰ as mother and TELL ME MORE ABOUT YOUR FAMILY. The computer is also programmed to produce the sequence I AM SORRY TO HEAR YOU ARE DEPRESSED whenever it encounters the nine-letter sequence depressed. It would apply this technique equally to the string I am not depressed or He depressed the button.
A second trick is repeating what is typed in with a small twist, a common enough trick in ordinary conversation. Given a string of letters including the two letter strings my and me, change them to the strings your and you and repeat the sentence. So My boyfriend made me come here becomes YOUR BOYFRIEND MADE YOU COME HERE. Similarly Yes sir she’s my baby becomes YES SIR SHE’S YOUR BABY, ‘Tis my delight on a shiny night ‘TIS YOUR DELIGHT ON A SHINY NIGHT, all without the computer doing more than change a few letters. The program has not comprehended the sentence in any way; it does not understand the grammatical structure or even that these strings of letters between spaces are ‘words’. A few other tricks add to the illusion. A string of words from the user’s input may be stored and then flung back later; Tell me what you meanT when you said ... you like bananas/Come FROM WIGAN/Play the PIANO.
The ELIZA program almost passes the Turing test. But this assembly of tricks cannot reflect how people use language. The Turing test is not demanding enough, particularly when it admits reflective psychotherapy in which the analyst deliberately turns the patient’s remarks back onto themselves. It is all too easy for the computer to pass. Using language in a human way involves knowing what it means, which involves at least having a dictionary of ‘words’ and meanings, a grammar for establishing the structure and for creating new sentences, and all the other paraphernalia introduced so far in this book.
ESCAPE FROM UTOPIA
This ELIZA dialogue between a human user and computer comes from a program for teaching English as a Foreign Language, called Escape from Utopia. The goal is for the student to escape from Utopia with a secret message; in this extract for an actual session, the user has been apprehended by the secret police and is being interrogated.
Computer: So we’ve caught you at last! What is the name you’re giving at the moment?
User: Smith.
C: Mr, Mrs, or Ms?
U: Mr.
C: What do you say is your nationality, Mr Smith?
U: Ruritanian.
C: And what job did you say you have?
U: I am a plumber.
C: Your name isn’t really Smith, is it?
U: Yes it is.
C: When did you start to be a spy?
U: I am not a spy.
C: You mean my information is incorrect then?
U: Yes it is.
C: You sound very positive about that.
U: I have never been a spy.
C: Only stupid people are plumbers! Where were you trained as a terrorist,
Mr Smith?
U: Do I have to answer?
C: I am not here to answer questions, you are.
U: I want to leave.
C: What colour does it say your eyes are on your passport, Smith?
U: Brown.
......
Source: BBCB program by V. Cook
A
more recent test of thinking has been applied by John Searle, called the Chinese
Room. Imagine a sealed room with two letterbox slots. Into one goes a message in
English; two minutes later the same message comes out the other in Chinese.
Inside the room, there might be a bilingual speaker of English and Chinese, who
spends the time actually translating the message. or there might be someone who
knows no Chinese but has a complex set of instructions: if the letters spell man choose the sign 
; if the letters spell walk choose
and
so on. In the one case there is meaning since the person has to understand the
English word before they can produced the Chinese version, in the other case,
there is a meaningless mechanical system with no language as such. And yet, from
the outside the Chinese room, the observer cannot tell which is which. According
to Searle, the computer never does anything but match mechanically; all computer
language is like ELIZA.
Computers and background knowledge of the world
For at least thirty years, computer experts have been predicting that the breakthrough with computer use of human language would happen tomorrow. The programs that ‘understand’ and use natural human speech or indeed writing with any human-like level of skill are still for tomorrow, not today. One of the main obstacles has proved to be the human being’s knowledge of the speech situation. The computer can be programmed to handle the words and even the grammar of written language to some extent — to recognise that happy is an adjective, John a proper name, and will be is a combination of auxiliary will and verb be, or even that, put together, they may make up a question, Will John be happy? But it does not know the context within which the sentence makes sense.
Suppose a computer is programmed to deal with restaurants. A customer might ask for Egg and chips please, a simple request. This presents no problem to the computer, which can match egg, chips etc in its dictionary and retrieve information about them. But this capacity is far from enough to deal with the language of the restaurant. Customers know, but computers do not, that the food in a restaurant is usually prepared or cooked, that it will be brought to the table, and that it must be paid for. None of this background is stated in the language involved. People don’t need to be told what restaurants are for, but computers do. It is only if these standard requirements are breached in some way that they get mentioned: the restaurant is a help-yourself buffet; the customer has run off without paying, or whatever. But computer programs have to be specifically told such background information in order to get anything out of even such a mundane remark as Egg and chips please.
The expectations of each situation were described by Roger Schank in terms of a ‘script’. A script has a certain number of dramatic ‘roles’; a restaurant conversation needs a customer and a restaurant employee whether a waiter, waitress, counter assistant, cashier, or whatever. The customer and the waiter know the behaviour expected of them; the types of request they can make, Egg and chips please not I demand to be taken to your leader, and the types of response, OK, not What a disgraceful suggestion.
The restaurant script consists of a number of separate ‘scenes’: finding a seat, getting the menu, ordering the food, getting the courses in sequence, asking for the bill, paying the bill. Each of these has its appropriate actions and language. A waiter would be assumed to be unbalanced if he presented us with the bill at the start of the meal, or gave us coffee before soup. Finally, like any play, scripts require props. Any context has its own paraphernalia; a restaurant has tables and chairs, plates, food, and so forth. Customers know which props to expect; if they haven’t got a knife, they make the waiter bring one.
The speakers’ view of the world contains many scripts, each with their roles, scenes and props — going to the doctor’s, travelling by bus, taking an examination, getting married, and so on. Unfortunately for the computer, the number of possible scripts is vast and it is not necessarily clear which one will be summoned up on a given occasion. Going to a restaurant for a meal may invoke additional scripts for meeting the opposite sex, disciplining children, exchanging secrets, negotiating contracts, having emergency medical treatment, and so on. A single situation seldom confines human beings to a single script. On one occasion the only speech addressed to me in a restaurant in France was C’est beau, être grandpere (Isn’t it nice to be a grandfather?), completely unpredictable in the situation, but natural enough as an apology from the cashier for holding up the queue by listening to by the previous customer going on about his grandchildren. In short, to be able to handle language in the way that human beings do, the computer needs to be programmed, not only with the sheer language knowledge of vocabulary and grammar but also with all the information that people take for granted about the world they see every day.
All in all, computers are not very comfortable with human language. They can pretend to use it but they have no idea what it means. The day when the computer will be able to use language effectively is still in the future, as witness the still laborious path to get an efficient system for machine translation between languages.
V. The distinctive features of human language
The main features of language discussed in this chapter can be summed up in the following list. Needless to say, each part of it would require much elaboration and qualification to be fully tenable. Other aspects are not included, such as the links between language and human thinking encountered in Chapter Four and the use of language for social purposes seen in Chapter Seven, which may well be shared with animal systems.
-
Communication of specific information. Languages are used to communicate ‘messages’ carrying information from one person to another. Bees also are capable of constructing messages transmitting information in this way but only about restricted topics. Apes are capable of communication to a limited degree when they are taught by humans. If dolphins can communicate, no-one has yet fathomed what they are saying.
-
Arbitrariness of language. Human languages are abstract systems with a built-in level of arbitrary sounds, letters or gestures. They do not correspond bit by bit to the world around them. Hence the list of words in a language is open-ended rather than restricted. Animal languages are limited to a particular set of words, with the exception perhaps of apes taught language.
-
Creativity of language. Humans can expand language indefinitely to say anything they can want. If you add together all the books in all the libraries of the world and all the sentences ever spoken, you would still not begin to exhaust the things that language could say. Animal languages at best are restricted to a few topics and a few combinations.
-
Perceiving in categories. Speech is organised on an all-or-nothing basis. A sound is always one thing or another, never half-way between two sounds. Though not unique to human beings, categorial perception is rare in other species.
-
Phrase structure. This final point will be developed in Chapter Twelve. In brief, human languages depend upon a grammatical system that arranges the elements into a structure rather than just putting one sound or element after another. No other species have either this type of phrase structure in general or the specific grammatical configurations, such as structure-dependency seen in Chapter Two. The defenders of apes regard this requirement as an unfair demand; Sue Savage-Rumbaugh does not see why syntax should be ‘the linguist’s holy grail’ and laments that ‘the supposed primacy of syntax still held them in its thrall.’
Overall then, while there is considerable uncertainty about many of the details, it seems that human language is indeed the sole property of the human race, if language is defined by the above characteristics. The proof of its uniqueness can only be found by testing the language of another intelligent species, perhaps on some planet in Alpha Centauri, to see whether these characteristic are due to the human beings who use language or are inevitable components in any language.
Some Crucial Features of Language
humans |
bees |
wild apes |
taughtapes |
|
Communication of specific information |
Y |
Y |
? |
Y |
Arbitrariness |
Y |
Y |
N |
? |
Creativity |
Y |
N |
N |
? |
Perceiving in categories |
Y |
N |
N |
? |
Phrase structure |
Y |
N |
N |
N |
Sources and further references
I. language and other species
The classic work on bees is: von Frisch, K. (1953) The Dancing Bees, Harcourt Brace Jovanovitch, New York, trans. D. Ilse. An account of natural ape communication is in: Petersen, M.R., and Jusczyk, P.W. (1984), ‘On perceptual predispositions for human speech and monkey vocalisations’, in P. Marler and H. Terrace (eds.), The Biology of Learning, Springer, 585-616. A book on talking to cats is: Moyes, P. (1978), How to Talk to your Cat, London, A.Barker
II. Unique Features of human language
For differences in children’s vocal tracts see: Kent, R.D. & Miolo, G. (1995), ‘Phonetic Abilities in the First Year of Life’, in Fletcher, P. & MacWhinney, B. (eds.), The Handbook of Child Language, Blackwell. The classic work on Neanderthals and sound space is: Lieberman, P. (1984), The Biology and Evolution of Language, Harvard U.P. Lorenz’s encounters with animals are described inter alia in: Lorenz, K. (1954), Man Meets Dog, Methuen, London. The notion of creativity was first found in Chomsky’s famous review: Chomsky, N. (1959), ‘Review of B.F. Skinner Verbal Behavior’, Language, 35, 26-58, and is in many of his later publications.
III. Teaching monkeys human language
The most accessible and fair-minded account of the research with apes is: Wallman. J. (1992), Aping Language, CUP. Some of the original accounts are: Savage-Rumbaugh, S., & D.M. Rumbaugh, ‘Language Analogue Project: Phase II’, in Children’s’ Language Vol. 2, ed. K Nelson, Gardener Press 1980, 267-308: Savage-Rumbaugh, S., & Lewin, R. (1994), Kanzi: the Ape at the Brink of the Human Mind, Doubleday, London. The work with human children is in: Barna, S. (1975), ‘Childhood aphasia: a preliminary investigation of some auditory and linguistic variables’, Brunel University. Reported in Cromer (1991): Hughes, J. (1974-5), ‘Acquisition of a non-vocal ‘language’ by aphasic children’, Cognition, 3, 41-55
IV Computers and Language
The Turing test case comes from: Turing, A.M. (1950), ‘Computing machinery and intelligence’, Mind, LIX. The original ELIZA work is described in: Weizenbaum, J. (1976), Computer Power and Human Reason, Freeman, San Francisco. The Chinese room is in: Searle, J., 1980, ‘Minds, Brains and Programs’, Behavioral and Brain Sciences, 3: 417–57. The concept of scripts comes from: Schank, R., and Abelson. R. (1977), Scripts, Plans, Goals, and Understanding, New Jersey, Lawrence Erlbaum
V human languages
The most cited source on the design features of human language is: Hockett, C.F. (1960’, ‘The origin of speech’, Scientific American, 203, 88-9
See also Apes Linguistic Relativity