Limitations of Computers as
(What follows is Part 2
of an invited paper included in Computers in Translation:
A Critical Appraisal. edited by John Newton and published by
Routledge, 1992. You can view Parts 1 & 3 from the links
at the bottom of this page.)
NOTE: This section explains how changing standards in the study of linguistics may be related to the limitations in Machine Translation we see today and perhaps prefigure certain lines of development in this field. Those only interested in the practical side may safely skip this section.
Some practical limitations of MT and even of CAT should already be clear enough. Less evident are the limitations in some of the linguistic theories which have sired much of the work in this field. On the whole Westerners are not accustomed to believing that problems may be insoluble, and after four decades of labor, readers might suppose that more progress had been made in this field than appears to be the case. To provide several examples at once, I can remember standing for some time by the display booth of a prominent European computer translation firm during a science conference at M.I.T. and listening to the comments of passers-by.
I found it dismaying to overhear the same attitudes voiced over and over again by quite sane and reasonable representatives from government, business and education. Most of what I heard could be summed up as 1) Language can't really be that complex since we all speak it; 2) Language, like nature, is an alien environment which must be conquered and tamed; 3) There has to be some simple way to cut through all the nonsense about linguistics, syntax, and semantics and achieve instant high quality translation; and 4) Why wasn't it all done yesterday?
To understand the reasons behind these comments and why they were phrased in this particular wayand also to understand the deeper reasons behind the limitations of computer translationt may be helpful to go back to the year 1944, when the first stirrings of current activity were little evident and another school of linguistics ruled all but supreme. In that year Leonard Bloomfieldone of the three deans of American Linguistics along with Edward Sapir and Benjamin Lee Whorf (7)was struggling to explain a problem that greatly perturbed him.
Bloomfield was concerned with what he called `Secondary Responses to Language.' By these he meant the things people say and seem to believe about language, often in an uninformed way. He called such opinions about language `secondary' to differentiate them from the use of language in communication, which he saw as `primary.'
People delivering such statements, he observed, are often remarkably alert and enthusiastic: their eyes grow bright, they tend to repeat these opinions over and over again to anyone who will hear, and they simply will not listeneven those who, like the ones I met at MIT, are highly trained and familiar with scientific proceduresto informed points of view differing with their own. They are overcome by how obvious or interesting their own ideas seem to be. (8)
I would add here that what Bloomfield seems to be describing is a set of symptoms clinically similar to some forms of hysteria. As he put it:
`It is only in recent years that I have learned to observe these secondary ..... responses in anything like a systematic manner, and I confess that I cannot explain themthat is, correlate them with anything else. The explanation will doubtless be a matter of psychology and sociology.' (9)
If it is indeed hysteria, as Bloomfield seems to suggest, I wonder if it might not be triggered because some people, when their ideas about language are questioned or merely held up for discussion, feel themselves under attack at the very frontier of their knowledge about reality. For many people language is so close to what they believe that they are no longer able to tell the difference between reality and the language they use to describe it.
It is an unsettling experience for them, one they cannot totally handle, somewhat like tottering on the edge of their recognized universe. The relationship between one's language habits and one's grasp of reality has not been adequately explored, perhaps because society does not yet train a sufficient number of bilingual, multilingual or linguistically oriented people qualified to undertake such investigations. (10)
Bloomfield went even further to define `tertiary responses to language' as innately hostile, angry, or contemptuous comments from those whose Secondary Responses are questioned in any serious way. They would be simply rote answers or rote repetitions of people's `secondary' statements whenever they were challenged on them, as though they were not capable of reasoning any further about them. Here he seemed to be going even further in identifying these responses with irrational or quasi-hysterical behavior.
What was it that Bloomfield found so worrisome about such opinions on language? Essentially healong with Whorf and Sapirhad spent all his life building what most people regarded as the `science of linguistics.' It was a study which required extended field work and painstaking analysis of both exotic and familiar languages before one was permitted to make any large generalizations even about a single language, much less about languages in general. Closely allied to the anthropology of Boas and Malinowski, it insisted on careful and thoughtful observations and a non-judgmental view of different cultures and their languages.
It was based on extremely high standards of training and scholarship and could not immediately be embraced by society at large. In some ways he and his colleagues had gone off on their own paths, and not everyone was able to follow them. Whorf and Sapir had in fact both died only a few years earlier, and Bloomfield himself would be gone five years later. Here are a few of the `secondary' statements that deeply pained Bloomfield and his generation of linguists:
Language A is more _____ than language B. (.........`logical,' `profound,' `poetic,' `efficient,' etc., fill in the blank yourself)
The structure of Language C proves that it is a universal language, and everyone should learn it as a basis for studying other languages.
Language D and Language E are so closely related that all their speakers can always easily understand each other.
Language F is extremely primitive and can only have a few hundred words in it.
Language G is demonstrably `better' than Languages H, J, and L.
The word for `________' (choose almost any word) in Language M proves scientifically that it is a worsebetter, more `primitive' or `evolved,' etc.language than Language N.
Any language is easy to master, once you learn the basic structure all languages are built on.
Summarized from Bloomfield, 1944, pp. 413-21
All of these statements are almost always demonstrably false upon closer knowledge of language and linguistics, yet such opinions are still quite commonly voiced. In this same piece Bloomfield also voiced his sadness over continual claims that `pure Elizabethan English' was spoken in this or that region of the American South (a social and historical impossibilityat best such dialects contain a few archaic phrases) or boasts that the Sequoyan Indian language was so perfect and easy to learn that all citizens of the State of Oklahoma should study it in school. (11)
What Bloomfield found particularly disturbing was that this sort of linguistic folklore never seemed to die out, never yielded to scientific knowledge, simply went on and on repropagating itself with a life of its own. Traces of it could even be found in the work of other scholars writing about language and linguistics.
Bloomfield's views were very much a reflection of his time. They stressed a relativistic view of language and culture and the notion that languages spoken by small indigenous groups of people had a significance comparable to that of languages spoken by much larger populations. They willingly embraced the notion that language, like reality itself, is a complex matrix of factors and tended to reject simplistic generalizations of any sort about either language or culture. Moreover, Bloomfield certainly saw his approach as being a crucial minimum stage for building any kind of true linguistic science.
Less than ten years after his death these ideas were replaced, also in the name of science, by a set of different notions, which Bloomfield would have almost certainly have dismissed as `Secondary Responses to Language.' These new observations, which shared a certain philosophical groundwork with computational linguistics, constitute the credo of the Chomskian approach, now accepted as the dominant scientific view. They include the following notions:
All languages are related by a `universal grammar.'
It is possible to delineate the meaning of any sentence in any language through knowledge of its deep structure and thereby replicate it in another language.
A diagram of any sentence will reveal this deep structure.
Any surface level sentence in any language can easily be related to its deep structure, and this in turn can be related to universal grammar in a relatively straightforward manner through a set of rules.
These and related statements are sufficient to describe not only the structure of language but the entire linguistic process of development and acculturation of infants and young children everywhere and can thus serve as a guide to all aspects of human language, including speech, foreign language training, and translation.
The similarity of these deep and surface level diagrams to the structure of computer languages, along with the purported similarity of the human mind to a computer, may be profoundly significant. (12)
These ideas are clearly not ones Bloomfield could have approved of. They are not relativistic or cautious but universalist and all-embracing, they do not emphasize the study of individual languages and cultures but leap ahead into stunning generalizations. As such, he would have considered them examples of `Secondary Responses' to language. In many ways they reflect the America of the late 'Fifties, a nation proud of its own new-found dominance and convinced that its values must be more substantial than those of `lesser' peoples. Such ideas also coincide nicely with a seemingly perennial need academia feels for theories offering a seemingly scientific approach, suggestive diagrams, learned jargon, and a grandiose vision.
We all know that science progresses by odd fits and starts and that the supreme doctrines of one period may become the abandoned follies of a later one. But the turnabout we have described is surely among the most extreme on record. It should also be stressed that the outlook of Bloomfield, Whorf and Sapir has never truly been disproved or rejected and still has followers today. (13) Moreover, there is little viable proof that these newer ideas, while they may have been useful in describing the way children learn to speak, have ever helped a single teacher to teach languages better or a single translator to translate more effectively. Nor has anyone ever succeeded in truly defining `deep structure' or `universal grammar.'
No one can of course place the whole responsibility for machine translation today on Noam Chomsky's theories about languagecertainly his disciples and followers (14) have also played a role, as has the overall welcome this entire complex of ideas has received. Furthermore, their advent has certainly also coincided with the re-emergence of many other `Secondary Responses', including most of the comments I mentioned overhearing at M.I.T. Much of the literature on Machine Translation has owedand continues to owea fair amount to this general approach to linguistic theory.
Overall understanding of language has certainly not flourished in recent times, and the old wives' tale of a single magical language providing the key to the understanding of all other tongues now flourishes again as a tribute both to Esperanto and the Indian Aymara language of Peru. (15) Disappointment with computer translation projects has also been widespread throughout this time, and at one point even Chomsky seemingly washed his hands of the matter, stating that `as for machine translation and related enterprises, they seemed to me pointless as well as probably quite hopeless.' (16)
Even such lofty notions as those favored by Turing and Weaver, that removing `language barriers' would necessarily be a good thing, or that different languages prevent people from realizing that they are `really all the same deep down,' could turn out to be `Secondary Responses.' It may also be that language barriers and differences have their uses and virtues, and that enhanced linguistic skills may better promote world peace than a campaign to destroy such differences. But popular reseeding of such notions is, as Bloomfield foresaw, quite insidious, and most of these ideas are still very much with us, right along with the proof that they may be unattainable. This is scarcely to claim that the end is near for computers as translation tools, though it may mean that further progress along certain lines of enquiry is unlikely.
There are probably two compelling sets of reasons why computers can never claim the upper hand over language in all its complexity, one rooted in the cultural side of language, the other in considerations related to mathematics. Even if the computer were suddenly able to communicate meaning flawlessly, it would still fall short of what humans do with language in a number of ways. This is because linguists have long been aware that communication of meaning is only one among many functions of language. Others are:
Demonstrating one's class status to the person one is speaking or writing to.
Simply venting one's emotions, with no real communication intended.
Establishing non-hostile intent with strangers, or simply passing time with them.
Engaging in non-communication by intentional or accidental ambiguity, sometimes also called `telling lies.'
Two or more of the above (including communication) at once.
Under these circumstances it becomes very difficult to explain how a computer can be programmed merely to recognize and distinguish these functions in Language A, much less make all the adjustments necessary to translate them into Language B. As we have seen, computers have problems simply with the communications side, not to mention all these other undeniable aspects of language. This would be hard enough with written texts, but with spoken or `live' language, the problems become all but insurmountable.
Closely related here is a growing awareness among writers and editors that it is virtually impossible to separate the formulation of even the simplest sentence in any language from the audience to whom it is addressed. Said another way, when the audience changes, the sentence changes. Phrased even more extremely, there is no such thing as a `neutral' or `typical' or `standard' sentenceeven the most seemingly innocuous examples will be seen on closer examination to be directed towards one audience or another, whether by age, education, class, profession, size of vocabulary, etc.
While those within the target audience for any given sentence will assume its meaning is obvious to all, those on its fringes must often make a conscious effort to absorb it, and those outside its bounds may understand nothing at all. This is such an everyday occurrence that it is easy to forget how common it really is. And this too adds a further set of perplexities for translators to unravel, for they must duplicate not only the `meaning' but also the specialized `angling' to an analogous audience in the new language.
Perhaps the most ironic proof of this phenomenon lies in the nature of the `model' sentences chosen by transformational and computational linguists to prove their points. Such sentences rarely reflect general usagethey are often simply the kinds of sentences used by such specialists to impress other specialists in the same field.
Further proof is provided here by those forms of translation often described as `impossible,' even when performed by humansstageplays, song lyrics, advertising, newspaper headlines, titles of books or other original works, and poetry. Here it is generally conceded that some degree of adaptation may be merged with translation. Theatre dialogue in particular demands a special level of `fidelity.' Sentences must be pronounceable by actors as well as literally correct, and the emotional impact of the play must be recreated as fully as possible. A joke in Language A must also become a joke in Language B, even if it isn't. A constantly maintained dramatic build-up must seek its relief or `punch-lines' at the right moments.
This may seem far from the concerns of a publication manager anxious to translate product documentation quickly and correctly. But in a real sense all use of words is dependent on building towards specific points and delivering `punch-lines' about how a product or process works. The difference is one of degree, not of quality. It is difficult to imagine how computers can begin to cope with this aspect of translation.
Cross-cultural concerns add further levels of complexity, and no miraculous `universal structure' (17) exists for handling them. Languages are simply not orderly restructurings of each other's ideas and processes, and a story I have told elsewhere (18) may perhaps best illustrate this. It relates to a real episode in my life when my wife and I were living in Italy. At that time she did most of the shopping to help her learn Italian, and she repeatedly came home complaining that she couldn't find certain cuts of meat at the butcher's.
I told her that if she concentrated on speaking better Italian, she would certainly find them. But she still couldn't locate the cuts of meat she wanted. Finally, I was forced to abandon my male presumption of bella figura and go with her to the market place, where I patiently explained in Italian what it was we were looking for to one butcher after the next. But even together we were still not successful. What we wanted actually turned out not to exist.
The Italians slice their meat differently than we do. There are not only different names for the cuts but actually different cuts as well. Their whole system is built around itthey feed and breed their cattle differently so as to produce these cuts. So one might argue that the Italian steer itself is differenttechnically and anatomically, it might just qualify as a different subspecies.
This notion of `slicing the animal differently' or of `slicing reality differently' can turn out to be a factor in many translation problems. It is altogether possible for whole sets of distinctions, indeed whole ranges of psychological or even tangiblerealities to vanish when going from one language to another. Those which do not vanish may still be mangled beyond recognition. It is this factor which poses one of the greatest challenges even for experienced translators. It may also place an insurmountable stumbling block in the path of computer translation projects, which are based on the assumption that simple conversions of obvious meanings between languages are readily possible.
Another cross-cultural example concerns a well-known wager AI pioneer Marvin Minsky has made with his M.I.T. students. Minsky has challenged them to create a program or device that can unfailingly tell the difference, as humans supposedly can, between a cat and a dog. Minsky has made many intriguing remarks on the relation between language and reality, (19) but he shows in this instance that he has unwittingly been manipulated by language-imposed categories.
The difference between a cat and a dog is by no means obvious, and even `scientific' Linnaean taxonomy may not provide the last word. The Tzeltal Indians of Mexico's Chiapas State in fact classify some of our `cats' in the `dog' category, rabbits and squirrels as `monkeys,' and a more doglike tapir as a `cat,' thus proving in this case that whole systems of animals can be sliced differently.
Qualified linguistic anthropologists have concluded that the Tzeltal system of naming animalsmaking allowance for the fact that they know only the creatures of their regionis ultimately just as useful and informative as Linnaean latinisms and even includes information that the latter may omit. (20) Comparable examples from other cultures are on record. (21)
An especially dramatic cross-cultural example suggests that at least part of the raging battle as to whether acupuncture and the several other branches of Chinese Medicine can qualify as `scientific' springs from the linguistic shortcomings of Western observers. The relationships concerning illness the Chinese observe and measure are not the ones we observe, their measurements and distinctions are not the same as ours, their interpretation of such distinctions are quite different from ours, the diagnosis suggested by these procedures is not the same, and the treatment and interpretation of a patient's progress can also radically diverge from our own.
Yet the whole process is perfectly logical and consistent in its own terms and is grounded in an empirical procedure. (18) The vocabulary is fiendishly difficult to explain to non-specialists in this highly developed branch of the Chinese language. No one knows how many other such instances of large and small discontinuities between languages and their meanings may exist, even among more closely related tongues like French and English, and no one can judge how great an effect such discontinuities may have on larger relationships between the two societies or even on ordinary conversations between their all too human representatives.
Just as the idea that the earth might be round went against the grain for the contemporaries of Columbus, so the notion that whole ranges of knowledge and experience may be inexpressible as one moves from one language to another seems equally outrageous to many today. Such a notion, that Language A cannot easily and perfectly replicate what is said in Language B, simply goes against what most people regard as `common sense.' But is such insistence truly commonsensical or merely another instance of Bloomfield's `Secondary Responses?' Something like this question lies at the root of the long-continuing and never fully resolved debate among linguists concerning the so-called Whorf-Sapir hypothesis. (7)
Mathematical evidence suggesting that computers can never fully overtake language is quite persuasive. It is also in part fairly simple and lies in a not terribly intricate consideration of the theory of sets. No subset can be larger than the set of which it is a part. Yet all of mathematicsand in fact all of science and technology, as members of a Linguistics school known as Glossematics (22) have arguedcan be satisfactorily identified as a subcategoryand possibly a subsetof language.
According to this reasoning, no set of its components can ever be great enough to serve as a representation of the superset they belong to, namely language. Allowing for the difficulties involved in determining the members of such sets, this argument by analogy alone would tend to place language and translation outside the limits of solvable problems and consign them to the realm of the intractable and undecidable. (23)
The theory of sets has further light to shed. Let us imagine all the words of Language A as comprising a single set, within which each word is assigned a number. Now let us imagine all the words of Language B as comprising a single set, with numbers once again assigned to each word. We'll call them Set A and Set B. If each numbered word within Set A meant exactly the same thing as each word with the same number in Set B, translation would be no problem at all, and no professional translators would be needed.
Absolutely anyone able to read would be able to translate any text between these two languages by looking up the numbers for the words in the first language and then substituting the words with the same numbers in the second language. It would not even be necessary to know either language. And computer translation in such a case would be incredibly easy, a mere exercise in `search and replace,' immediately putting all the people searching through books of words and numbers out of business.
But the sad reality of the matterand the real truth behind Machine Translation effortsis that Word # 152 in Language A does not mean exactly what Word # 152 in Language B means. In fact, you may have to choose between Words 152, 157, 478, and 1,027 to obtain a valid translation. It may further turn out that Word 152 in Language B can be translated back into Language A not only as 152 but also 149, 462, and 876.
In fact, Word # 152 in Language B may turn out to have no relation to Word # 152 in Language A at all. This is because 47 words with lower numbers in Language B had meanings that spilled over into further numbered listings. It could still be argued that all these difficulties could be sorted out by complex trees of search and goto commands. But such altogether typical examples are only the beginning of the problems faced by computational linguists, since words are rarely used singly or in a vacuum but are strung together in thick, clammy strings of beads according to different rules for different languages.
Each bead one uses influences the number, shape, and size of subsequent beads, so that each new word in a Language A sentence compounds the problems of translation into Language B by an extremely non-trivial factor, with a possible final total exceeding by several orders of magnitude the problems confronted by those who program computers for the game of chess.
There are of course some real technical experts, the linguistic equivalents of Chess Grand Masters, who can easily determine most of the time what the words mean in Language A and how to render them most correctly in Language B. These experts are called translators, though thus far no one has attributed to them the power or standing of Chess Masters. Another large irony: so far the only people who have proved capable of manipulating the extremely complex systems originally aimed at replacing translators have been, in fact.....translators.
(7) Both Sapir and Whorf carried out extensive study of American Indian languages and together evolved what has come to be called the Whorf-Sapir Hypothesis. Briefly stated, this theory states that what humans see, do and know is to a greater or lesser extent based on the structure of their language and the categories of thought it encourages or excludes. The prolonged and spirited debate around this hypothesis has largely centered on the meaning of the phrase to a greater or lesser extent. Even the theory's most outright opponents concede it may have validity in some cases, though they see something resembling strict determinism in applying it too broadly and point out that translation between languages would not be possible if the Whorf-Sapir Hypothesis were true. Defenders of the theory charge that its critics may not have learned any one language thoroughly enough to become fully aware of how it can hobble and limit human thinking and further reply that some translation tasks are far more difficult than others, sometimes bordering on the impossible.
(8) Bloomfield, Secondary and Tertiary Responses to Language, in Hockett 1970 , pp: 412-29. This piece originally appeared in Language 20.45-55 and was reprinted in Hockett 1970 and elsewhere. The author's major work in the field of linguistics was Bloomfield 1933/1984.
(9) Bloomfield, in Hockett 1970, page 420.
(10) Since so many people in so many countries speak two or more languages, it might be imagined that there is a broad, widely-shared body of accurate knowledge about such people. In point of fact there is not, and the first reasonably accessible book-length account of this subject is Grosjean. Some of this book's major points, still poorly appreciated by society at large:
Relatively few bilingual people are able to translate between their two languages with ease. Some who try complain of headaches, many cannot do it at all, many others do it badly but are not aware of this. Thus, bilingualism and translation skills are two quite different abilities, perhaps related to different neurological processes.
No bilinguals possess perfectly equal skills in both their languages. All favor the one or the other at least slightly, whether in reading, writing, or speaking. Thus, the notion of being brought up perfectly bilingual is a mythmuch of bilingualism must be actively achieved in both languages..
One does not have to be born bilingual to qualify as such. Those who learn a second language later, even as adults, can be considered bilingual to some extent, provided they actively or passively use a second language in some area of their lives.
(11) Bloomfield, in Hockett 1970, pp. 414-16.
(12) Though presented here in summarized form, these ideas all form part of the well-known Chomskian process and can be found elaborated in various stages of complexity in many works by Chomsky and his followers. See Chomsky, 1957, 1965, & 1975.
(13) The bloodied battlefields of past scholarly warfare waged over these issues are easily enough uncovered. In 1968 Charles Hockett, a noted follower of Bloomfield, launched a full-scale attack on Chomsky (Hockett, 1968) Those who wish to follow this line of debate further can use his bibliography as a starting point. Hostilities even spilled over into a New Yorker piece and a book of the same name (Mehta). Other starting points are the works of Chomsky's teacher (Harris) or a unique point of view related to computer translation by Lehmann. Throughout this debate, there have been those who questioned why these transformational linguists, who claim so much knowledge of language, should write such dense and unclear English. When questioned on this, Mehta relates Chomsky's reply as follows: `"I assume that the writing in linguistics is no worse than the writing in any other academic field" Chomsky says. "The ability to use language well is very different from the ability to study it. Once the Slavic Department at Harvard was thinking of offering Vladimir Nabokov an appointment. Roman Jakobson, the linguist, who was in the department then, said that he didn't have anything against elephants but he wouldn't appoint one a professor of zoology." Chomsky laughs.'
(14) See for example Fodor or Chisholm.
(15) See Note 5 for reference to Esperanto. The South American Indian language Aymara has been proposed and partially implemented as a basis for multilingual Machine Translation by the Bolivian mathematician Ivan Guzman de Rojas, who claims that its special syntactic and logical structures make it an idea vehicle for such a purpose. On a surface analysis, such a notion sounds remarkably close to Bloomfieldian secondary responses about the ideal characteristics of the Sequoyan language, long before computers entered the picture. (Guzman de Rojas)
(16) See Chomsky, 1975, p. 40.
(17) The principal work encouraging a search for `universal' aspects of language is Greenberg. Its findings are suggestive but inconclusive.
(18) This section first appeared in a different form as a discussion between Sandra Celt and the author (Celt & Gross).
(19) Most of Marvin Minsky's thoughts on language follow a strictly Chomskian frameworkthus, we can perhaps refer to the overall outlook of his school as a Minksian-Chomskian one. For further details see Sections 19-26 of Minsky.
(20) See Hunn for a considerably expanded treatment.
(21) A rich literature expanding on this theme can be found in the bibliography of the book mentioned in the preceding note.
(22) Glossematics is in the U.S. a relatively obscure school of linguistics, founded by two Danes, Louis Hjelmslev and Hans Jørgen Uldall, earlier in the century. Its basic thesis has much in common with thinking about computers and their possible architectures. It starts from the premise that any theory about language must take into account all possible languages that have ever existed or can exist, that this is the absolute minimum requirement for creating a science of linguistics. To objections that this is unknowable and impossible, its proponents reply that mathematicians regularly deal with comparable unknowables and are still able to make meaningful generalizations about them. From this foundation emerges the interesting speculation that linguistics as a whole may be even larger than mathematics as a whole, and that `Linguistics' may not be that science which deals with language but that the various so-called sciences with their imperfect boundaries and distinctions may in fact be those branches of linguistics that deal for the time being with various domains of linguistics. Out of this emerges the corollary that taxonomy is the primary science, and that only by naming things correctly can one hope to understand them more fully. Concomitant with these notions also arises an idea that ought to have attracted computer translation researchers, that a glossematic approach could lay down the down the basis for creating culture-independent maps of words and realities through various languages, assigning precise addresses for each `word' and `meaning,' though it would require a truly vast system for its completion and even then would probably only provide lists of possible translations rather than final translated versions. The major theoretical text of Glossematics, somewhat difficult to follow like many linguistic source books, is Hjelmslev. One excellent brief summary in English is Whitfield, another available only in Spanish or Swedish is Malmberg.
(23) Different strands of this argument may be pursued in Nagel and Newman, Harel, and Goedel.
Bloomfield, Leonard (1933) Language, New York: Holt, Rinehart, & Winston, (reprinted in great part in 1984, University of Chicago).
Bloomfield, Leonard (1944) Secondary and Tertiary Responses to Language. This piece originally appeared in Language 20.45-55, and has been reprinted in Hockett 1970 and elsewhere. This particular citation appears on page 420 of the 1970 reprint.
Booth, Andrew Donald, editor (1967) Machine Translation, Amsterdam.
Brower, R.A. editor (1959) On Translation, Harvard University Press.
Carbonell, Jaime G. & Tomita, Masaru (1987) Knowledge-Based Machine Translation, and the CMU Approach, found in Sergei Nirenburg's excellent though somewhat technical anthology (Nirenburg).
Celt, Sandra & Gross, Alex (1987) The Challenge of Translating Chinese Medicine, Language Monthly, April. .
Chisholm, William S., Jr. (1981) Elements of English Linguistics, Longman.
Chomsky, Noam(1957) Syntactic Structures, Mouton, The Hague.
Chomsky, Noam (1965) Aspects of the Theory of Syntax, MIT Press.
Chomsky, Noam (1975) The Logical Structure of Linguistic Theory, p. 40, University of Chicago Press.
Coughlin, Josette (1988) Artificial Intelligence and Machine Translation, Present Developments and Future Prospects, in Babel 34:1. 3-9 , pp. 1-9.
Datta, Jean(1988) MT in Large Organizations, Revolution in the Workplace, in Vasconcellos 1988a.
Drexler, Eric K. (1986) Engines of Creation, Forward by Marvin Minsky, Anchor Press, New York.
Fodor, Jerry A & Katz, Jerrold J. (1964) The Structure of Language, Prentice-Hall, N.Y.
Goedel, Kurt (1931) Ueber formal unentscheidbare Saetze der Principia Mathematica und verwandte Systeme I, Monatshefte fuer Mathematik und Physik, vol. 38, pp. 173-198.
Greenberg, Joseph (1963) Universals of Language, M.I.T.Press.
Grosjean, Francois (1982) Life With Two Languages: An Introduction to Bilingualism, Harvard University Press.
Guzman der Rojas, Ivan (1985) Logical and Linguistic Problems of Social Communication with the Aymara People, International Development Research Center, Ottawa.
Harel, David (1987) Algorithmics: The Spirit of Computing, Addison-Wesley.
Harris, Zellig (1951) Structural Linguistics, Univ. of Chicago Press.
Hjelmslev, Louis (1961) Prolegomena to a Theory of Language, translated by Francis Whitfield, University of Wisconsin Press, (Danish title: Omkring sprogteoriens grundlaeggelse, Copenhagen, 1943)
Hockett, Charles F. (1968) The State of the Art, Mouton, The Hague.
Hockett, Charles F. (1970) A Leonard Bloomfield Anthology, Bloomington, [(contains Bloomfield 1944)].
Hodges, Andrew (1983) Alan Turing: The Enigma,Simon & Schuster, New York.
Hunn, Eugene S. (1977) Tzeltal Folk Zoology: The Classification of Discontinuities in Nature, Academic Press, New York.
Hutchins, W.J. (1986) Machine Translation: Past, Present, Future, John Wiley & Sons.
Jakobson, Roman (1959) On Linguistic Aspects of Translation, in Brower.
Kay, Martin (1982) Machine Translation, from American Journal of Computational Linguistics, April-June, pp. 74-78.
Kingscott, Geoffrey (1990) SITE Buys B'Vital, Relaunch of French National MT Project, Language International, April.
Klein, Fred (1988) Factors in the Evaluation of MT: A Pragmatic Approach, in Vasconcellos 1988a.
Lehmann, Winfred P. (1987) The Context of Machine Translation, Computers and Translation 2.
Malmberg, Bertil (1967) Los Nuevos Caminos der la Linguistica, Siglo Veintiuno, Mexico, , pp. 154-74 (in Swedish: Nya Vagar inom Sprakforskningen, 1959)
Mehta, Ved (1971) John is Easy to Please, Ferrar, Straus & Giroux, New York, (originally a New Yorker article, reprinted in abridged form in Fremantle, Anne (1974) A Primer of Linguistics, St. Martin's Press, New York.
Minsky, Marvin (1986) The Society of Mind, Simon & Schuster, New York, especially Sections 19-26.
Nagel, Ernest and Newman, James R. (1989) Goedel's Proof, New York University Press.
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