Man-computer symbiosis is an expected development in cooperative interaction between men and electronic computers. It will involve very close coupling between the human and the electronic members of the partnership. The main aims are 1) to let computers facilitate formulative thinking as they now facilitate the solution of formulated problems, and 2) to enable men and computers to cooperate in making decisions and controlling complex situations without inflexible dependence on predetermined programs. In the anticipated symbiotic partnership, men will set the goals, formulate the hypotheses, determine the criteria, and perform the evaluations. Computing machines will do the routinizable work that must be done to prepare the way for insights and decisions in technical and scientific thinking. Preliminary analyses indicate that the symbiotic partnership will perform intellectual operations much more effectively than man alone can perform them. Prerequisites for the achievement of the effective, cooperative association include developments in computer time sharing, in memory components, in memory organization, in programming languages, and in input and output equipment.

 
1 Introduction 

1.1 Symbiosis 

The fig tree is pollinated only by the insect Blastophaga grossorun.
The larva of the insect lives in the ovary of the fig tree, and there
it gets its food. The tree and the insect are thus heavily
interdependent: the tree cannot reproduce wit bout the insect; the
insect cannot eat wit bout the tree;  together, they constitute not
only a viable but a productive and thriving partnership. This
cooperative "living together in intimate association, or even close
union, of two dissimilar organisms" is called symbiosis [27].

"Man-computer symbiosis" is a subclass of man-machine systems. There
are many man-machine systems. At present, however, there are no
man-computer symbioses. The purposes of this paper are to present the
concept and, hopefully, to foster the development of man-computer
symbiosis by analyzing some problems of interaction between men and
computing machines, calling attention to applicable principles of
man-machine engineering, and pointing out a few questions to which
research answers are needed. The hope is that, in not too many years,
human brains and computing machines will be coupled together very
tightly, and that the resulting partnership will think as no human
brain has ever thought and process data in a way not approached by the
information-handling machines we know today.

1.2 Between "Mechanically Extended Man" and "Artificial Intelligence"

As a concept, man-computer symbiosis is different in an important way
from what North [21] has called "mechanically extended man." In the
man-machine systems of the past, the human operator supplied the
initiative, the direction, the integration, and the criterion. The
mechanical parts of the systems were mere extensions, first of the
human arm, then of the human eye. These systems certainly did not
consist of "dissimilar organisms living together ..." There was only
one kind of organism --— man -- and the rest was there only to help
him.

In one sense of course, any man-made system is intended to help man,
to help a man or men outside the system. If we focus upon the human
operator within the system, however, we see that, in some areas of
technology, a fantastic change has taken place during the last few
years. "Mechanical extension" has given way to replacement of men, to
automation, and the men who remain are there more to help than to be
helped. In some instances, particularly in large computer-centered
information and control systems, the human operators are responsible
mainly for functions that it proved infeasible to automate. Such
systems (" humanly extended machines," North might call them) are not
symbiotic systems. They are "semi-automatic"  systems, systems that
started out to be fully automatic but fell short of the goal.

Man-computer symbiosis is probably not the ultimate paradigm for
complex technological systems. It seems entirely possible that, in
due course, electronic or chemical "machines" will outdo the human
brain in most of the functions we now consider exclusively within its
province. Even now, Gelernter's IBM-704 program for proving theorems
in plane geometry proceeds at about the same pace as Brooklyn high
school students, and makes similar errors.[ 12] There are, in fact,
several theorem-proving, problem-solving, chess-playing, and
pattern-recognizing programs (too many for complete reference [1, 2,
5, 8, 11, 13, 17, 18, 19, 22, 23, 25] ) capable of rivaling human
intellectual performance in restricted areas; and Newell, Simon, and
Shaw's[20] "general problem solver" may remove some of the
restrictions. In short, it seems worthwhile to avoid argument with
(other) enthusiasts for artificial intelligence by conceding
dominance in the distant future of cerebration to machines alone.
There will nevertheless be a fairly long interim during which the main
intellectual advances will be made by men and computers working
together in intimate association. A multidisciplinary study group,
examining future research and development problems of the Air Force,
estimated that it would be 1980 before developments in artificial
intelligence make it possible for machines alone to do much thinking
or problem solving of military significance. That would leave, say,
five years to develop man-computer symbiosis and 15 years to use it.
The 15 may be 10 or 500, but those years should be intellectually the
most creative and exciting in the history of mankind.

2 Aims of Man-Computer Symbiosis 

Present-day computers are designed primarily to solve preformulated
problems or to process data according to predetermined procedures.
The course of the computation may be conditional upon results obtained
during the computation, but all the alternatives must be foreseen in
advance. (If an unforeseen alternative arises, the whole process comes
to a halt and awaits the necessary extension of the program.) The
requirement for preformulation or predetermination is sometimes no
great disadvantage. It is often said that programming for a computing
machine forces one to think clearly, that it disciplines the thought
process. If the user can think his problem through in advance,
symbiotic association with a computing machine is not necessary.

However, many problems that can be thought through in advance are very
difficult to think through in advance. They would be easier to solve,
and they could be solved faster, through an intuitively guided
trial-and-error procedure in which the computer cooperated, turning up
flaws in the reasoning or revealing unexpected turns in the solution.
Other problems simply cannot be formulated without computing-machine
aid. Poincaré anticipated the frustration of an important group of
would-be computer users when he said, "The question is not, 'What is
the answer? ' The question is, 'What is the question? ' " One of the
main aims of man-computer symbiosis is to bring the computing machine
effectively into the formulative parts of technical problems.

The other main aim is closely related. It is to bring computing
machines effectively into processes of thinking that must go on in
"real time," time that moves too fast to permit using computers in
conventional ways. Imagine trying, for example, to direct a battle
with the aid of a computer on such a schedule as this. You formulate
your problem today. Tomorrow you spend with a programmer. Next week
the computer devotes 5 minutes to assembling your program and 47
seconds to calculating the answer to your problem. You get a sheet of
paper 20 feet long, full of numbers that, instead of providing a final
solution, only suggest a tactic that should be explored by simulation.
Obviously, the battle would be over before the second step in its
planning was begun. To think in interaction with a computer in the
same way that you think with a colleague whose competence supplements
your own will require much tighter coupling between man and machine
than is suggested by the example and than is possible today.

3 Need for Computer Participation in Formulative and Real-Time
Thinking

The preceding paragraphs tacitly made the assumption that, if they
could be introduced effectively into the thought process, the
functions that can be performed by data-processing machines would
improve or facilitate thinking and problem solving in an important
way. That assumption may require justification.

3.1 A Preliminary and Informal Time-and-Motion Analysis of Technical
Thinking

Despite the fact that there is a voluminous literature on thinking and
problem solving, including intensive case-history studies of the
process of invention, I could find nothing comparable to a
time-and-motion-study analysis of the mental work of a person engaged
in a scientific or technical enterprise.  In the spring and summer of
1957, therefore, I tried to keep track of what one moderately
technical person actually did during the hours he regarded as devoted
to work. Although I was aware of the inadequacy of the sampling, I
served as my own subject.

It soon became apparent that the main thing I did was to keep records,
and the project would have become an infinite regress if the keeping
of records had been carried through in the detail envisaged in the
initial plan.  It was not. Nevertheless, I obtained a picture of my
activities that gave me pause. Perhaps my spectrum is not typical— I
hope it is not, but I fear it is.

About 85 per cent of my "thinking" time was spent getting into a
position to think, to make a decision, to learn something I needed to
know.  Much more time went into finding or obtaining information than
into digesting it. Hours went into the plotting of graphs, and other
hours into instructing an assistant how to plot. When the graphs were
finished, the relations were obvious at once, but the plotting had to
be done in order to make them so. At one point, it was necessary to
compare six experimental determinations of a function relating
speech-intelligibility to speech-to-noise ratio. No two experimenters
had used the same definition or measure of speech-to-noise ratio.
Several hours of calculating were required to get the data into
comparable form. When they were in comparable form, it took only a few
seconds to determine what I needed to know.

Throughout the period I examined, in short, my "thinking" time was
devoted mainly to activities that were essentially clerical or
mechanical:  searching, calculating, plotting, transforming,
determining the logical or dynamic consequences of a set of
assumptions or hypotheses, preparing the way for a decision or an
insight. Moreover, my choices of what to attempt and what not to
attempt were determined to an embarrassingly great extent by
considerations of clerical feasibility, not intellectual capability.

The main suggestion conveyed by the findings just described is that
the operations that fill most of the time allegedly devoted to
technical thinking are operations that can be performed more
effectively by machines than by men. Severe problems are posed by the
fact that these operations have to be performed upon diverse variables
and in unforeseen and continually changing sequences. If those
problems can be solved in such a way as to create a symbiotic relation
between a man and a fast information-retrieval and data-processing
machine, however, it seems evident that the cooperative interaction
would greatly improve the thinking process.

It may be appropriate to acknowledge, at this point, that we are using
the term "computer" to cover a wide class of calculating,
data-processing, and information-storage-and-retrieval machines. The
capabilities of machines in this class are increasing almost daily. It
is therefore hazardous to make general statements about capabilities
of the class. Perhaps it is equally hazardous to make general
statements about the capabilities of men. Nevertheless, certain
genotypic differences in capability between men and computers do
stand out, and they have a bearing on the nature of possible
man-computer symbiosis and the potential value of achieving it.

As has been said in various ways, men are noisy, narrow-band devices,
but their nervous systems have very many parallel and simultaneously
active channels. Relative to men, computing machines are very fast
and very accurate, but they are constrained to perform only one or a
few elementary operations at a time. Men are flexible, capable of
"programming themselves contingently" on the basis of newly received
information. Computing machines are single-minded, constrained by
their " pre-programming." Men naturally speak redundant languages
organized around unitary objects and coherent actions and employing 20
to 60 elementary symbols. Computers "naturally" speak nonredundant
languages, usually with only two elementary symbols and no inherent
appreciation either of unitary objects or of coherent actions.

To be rigorously correct, those characterizations would have to
include many qualifiers. Nevertheless, the picture of dissimilarity
(and therefore potential supplementation) that they present is
essentially valid. Computing machines can do readily, well, and
rapidly many things that are difficult or impossible for man, and men
can do readily and well, though not rapidly, many things that are
difficult or impossible for computers. That suggests that a symbiotic
cooperation, if successful in integrating the positive
characteristics of men and computers, would be of great value. The
differences in speed and in language, of course, pose difficulties
that must be overcome.

4 Separable Functions of Men and Computers in the Anticipated
Symbiotic Association

It seems likely that the contributions of human operators and
equipment will blend together so completely in many operations that it
will be difficult to separate them neatly in analysis. That would be
the case if, in gathering data on which to base a decision, for
example, both the man and the computer came up with relevant
precedents from experience and if the computer then suggested a course
of action that agreed with the man's intuitive judgment.  (In
theorem-proving programs, computers find precedents in experience, and
in the SAGE System, they suggest courses of action. The foregoing is
not a far-fetched example. ) In other operations, however, the
contributions of men and equipment will be to some extent separable.

Men will set the goals and supply the motivations, of course, at least
in the early years. They will formulate hypotheses. They will ask
questions.  They will think of mechanisms, procedures, and models.
They will remember that such-and-such a person did some possibly
relevant work on a topic of interest back in 1947, or at any rate
shortly after World War II, and they will have an idea in what
journals it might have been published. In general, they will make
approximate and fallible, but leading, contributions, and they will
define criteria and serve as evaluators, judging the contributions of
the equipment and guiding the general line of thought.

In addition, men will handle the very-low-probability situations when
such situations do actually arise. (In current man-machine systems,
that is one of the human operator's most important functions. The sum
of the probabilities of very-low-probability alternatives is often
much too large to neglect. ) Men will fill in the gaps, either in the
problem solution or in the computer program, when the computer has no
mode or routine that is applicable in a particular circumstance.

The information-processing equipment, for its part, will convert
hypotheses into testable models and then test the models against data
(which the human operator may designate roughly and identify as
relevant when the computer presents them for his approval). The
equipment will answer questions.  It will simulate the mechanisms and
models, carry out the procedures, and display the results to the
operator. It will transform data, plot graphs (" cutting the cake" in
whatever way the human operator specifies, or in several alternative
ways if the human operator is not sure what he wants). The equipment
will interpolate, extrapolate, and transform. It will convert static
equations or logical statements into dynamic models so the human
operator can examine their behavior. In general, it will carry out the
routinizable, clerical operations that fill the intervals between
decisions.

In addition, the computer will serve as a statistical-inference,
decision-theory, or game-theory machine to make elementary evaluations
of suggested courses of action whenever there is enough basis to
support a formal statistical analysis. Finally, it will do as much
diagnosis, pattern-matching, and relevance-recognizing as it
profitably can, but it will accept a clearly secondary status in those
areas.

5 The Prerequisites for Realization of Man-Computer Symbiosis

The data-processing equipment tacitly postulated in the preceding
section is not available. The computer programs have not been written.
There are in fact several hurdles that stand between the nonsymbiotic
present and the anticipated symbiotic future. Let us examine some of
them to see more clearly what is needed and what the chances are of
achieving it.

5.1 Speed Mismatch Between Men and Computers 

Any present-day large-scale computer is too fast and too costly for
real-time cooperative thinking with one man. Clearly, for the sake of
efficiency and economy, the computer must divide its time among many
users. Time-sharing systems are currently under active development.
There are even arrangements to keep users from "clobbering" anything
but their own personal programs.

It seems reasonable to envision, for a time 10 or 15 years hence, a
"thinking center" that will incorporate the functions of present-day
libraries together with anticipated advances in information storage
and retrieval and the symbiotic functions suggested earlier in this
paper. The picture readily enlarges itself into a network of such
centers, connected to one another by wide-band communication lines and
to individual users by leased-wire services.  In such a system, the
speed of the computers would be balanced, and the cost of the gigantic
memories and the sophisticated programs would be divided by the number
of users.


5.2 Memory Hardware Requirements 

When we start to think of storing any appreciable fraction of a
technical literature in computer memory, we run into billions of bits
and, unless things change markedly, billions of dollars.  The first
thing to face is that we shall not store all the technical and
scientific papers in computer memory. We may store the parts that can
be summarized most succinctly— the quantitative parts and the
reference citations— but not the whole. Books are among the most
beautifully engineered, and human-engineered, components in
existence, and they will continue to be functionally important within
the context of man-computer symbiosis. (Hopefully, the computer will
expedite the finding, delivering, and returning of books.)

The second point is that a very important section of memory will be
permanent: part indelible memory and part published memory. The
computer will be able to write once into indelible memory, and then
read back indefinitely, but the computer will not be able to erase
indelible memory.  (It may also over-write, turning all the 0's into
l's, as though marking over what was written earlier. ) Published
memory will be "read-only" memory.  It will be introduced into the
computer already structured. The computer will be able to refer to it
repeatedly, but not to change it. These types of memory will become
more and more important as computers grow larger.  They can be made
more compact than core, thin-film, or even tape memory, and they will
be much less expensive. The main engineering problems will concern
selection circuitry.

In so far as other aspects of memory requirement are concerned, we may
count upon the continuing development of ordinary scientific and
business computing machines There is some prospect that memory
elements will become as fast as processing (logic) elements. That
development would have a revolutionary effect upon the design of
computers.

5.3 Memory Organization Requirements 

Implicit in the idea of man-computer symbiosis are the requirements
that information be retrievable both by name and by pattern and that
it be accessible through procedure much faster than serial search. At
least half of the problem of memory organization appears to reside in
the storage procedure. Most of the remainder seems to be wrapped up in
the problem of pattern recognition within the storage mechanism or
medium. Detailed discussion of these problems is beyond the present
scope. However, a brief outline of one promising idea, "trie memory,"
may serve to indicate the general nature of anticipated developments.

Trie memory is so called by its originator, Fredkin [10], because it
is designed to facilitate retrieval of information and because the
branching storage structure, when developed, resembles a tree. Most
common memory systems store functions of arguments at locations
designated by the arguments. (In one sense, they do not store the
arguments at all. In another and more realistic sense, they store all
the possible arguments in the framework structure of the memory.) The
trie memory system, on the other hand, stores both the functions and
the arguments. The argument is introduced into the memory first, one
character at a time, starting at a standard initial register. Each
argument register has one cell for each character of the ensemble (e.
g., two for information encoded in binary form) and each character
cell has within it storage space for the address of the next register.  
The argument is stored by writing a series of addresses, each one of
which tells where to find the next. At the end of the argument is a
special "end-of-argument" marker. Then follow directions to the
function, which is stored in one or another of several ways, either
further trie structure or "list structure" often being most effective.

The trie memory scheme is inefficient for small memories, but it
be-comes increasingly efficient in using available storage space as
memory size increases. The attractive features of the scheme are
these: 1) The retrieval process is extremely simple. Given the
argument, enter the standard initial register with the first
character, and pick up the address of the second.  Then go to the
second register, and pick up the address of the third, etc.  2) If two
arguments have initial characters in common, they use the same storage
space for those characters. 3) The lengths of the arguments need not
be the same, and need not be specified in advance. 4) No room in
storage is reserved for or used by any argument until it is actually
stored. The trie structure is created as the items are introduced into
the memory. 5) A function can be used as an argument for another
function, and that function as an argument for the next. Thus, for
example, by entering with the argument, "matrix multiplication," one
might retrieve the entire program for performing a matrix
multiplication on the computer. 6) By examining the storage at a given
level, one can determine what thus-far similar items have been stored.
For example, if there is no citation for Egan, J. P., it is but a step
or two backward to pick up the trail of Egan, James . . . .

The properties just described do not include all the desired ones, but
they bring computer storage into resonance with human operators and
their predilection to designate things by naming or pointing.

5.4 The Language Problem 

The basic dissimilarity between human languages and computer languages
may be the most serious obstacle to true symbiosis. It is reassuring,
however, to note what great strides have already been made, through
interpretive programs and particularly through assembly or compiling
programs such as FORTRAN, to adapt computers to human language forms.
The "Information Processing Language" of Shaw, Newell, Simon, and
Ellis [24] represents another line of rapprochement. And, in ALGOL and
related systems, men are proving their flexibility by adopting
standard formulas of representation and expression that are readily
translatable into machine language.

For the purposes of real-time cooperation between men and computers,
it will be necessary, however, to make use of an additional and rather
different principle of communication and control. The idea may be
high-lighted by comparing instructions ordinarily addressed to
intelligent human beings with instructions ordinarily used with
computers. The latter specify precisely the individual steps to take
and the sequence in which to take them. The former present or imply
something about incentive or motivation, and they supply a criterion
by which the human executor of the instructions will know when he has
accomplished his task. In short: instructions directed to computers
specify courses; instructions-directed to human beings specify goals.

Men appear to think more naturally and easily in terms of goals than
in terms of courses. True, they usually know something about
directions in which to travel or lines along which to work, but few
start out with precisely formulated itineraries. Who, for example,
would depart from Boston for Los Angeles with a detailed specification
of the route? Instead, to paraphrase Wiener, men bound for Los Angeles
try continually to decrease the amount by which they are not yet in
the smog.

Computer instruction through specification of goals is being
approached along two paths. The first involves problem-solving,
hill-climbing, self-organizing programs. The second involves real-time
concatenation of pre-programmed segments and closed subroutines which
the human operator can designate and call into action simply by name.

Along the first of these paths, there has been promising exploratory
work.  It is clear that, working within the loose constraints of
predetermined strategies, computers will in due course be able to
devise and simplify their own procedures for achieving stated goals.
Thus far, the achievements have not been substantively important; they
have constituted only "demonstration in principle." Nevertheless, the
implications are far-reaching.

Although the second path is simpler and apparently capable of earlier
realization, it has been relatively neglected. Fredkin's trie memory
provides a promising paradigm. We may in due course see a serious
effort to develop computer programs that can be connected together
like the words and phrases of speech to do whatever computation or
control is required at the moment. The consideration that holds back
such an effort, apparently, is that the effort would produce nothing
that would be of great value in the context of existing computers. It
would be unrewarding to develop the language before there are any
computing machines capable of responding meaningfully to it.


5.5 Input and Output Equipment 

The department of data processing that seems least advanced, in so far
as the requirements of man-computer symbiosis are concerned, is the
one that deals with input and output equipment or, as it is seen from
the human operator's point of view, displays and controls. Immediately
after saying that, it is essential to make qualifying comments,
because the engineering of equipment for high-speed introduction and
extraction of information has been excellent, and because some very
sophisticated display and control techniques have been developed in
such research laboratories as the Lincoln Laboratory. By and large, in
generally available computers, however, there is almost no provision
for any more effective, immediate man-machine communication than can
be achieved with an electric typewriter.

Displays seem to be in a somewhat better state than controls. Many
computers plot graphs on oscilloscope screens, and a few take
advantage of the remarkable capabilities, graphical and symbolic, of
the charactron display tube. Nowhere, to my knowledge, however, is
there anything approaching the flexibility and convenience of the
pencil and doodle pad or the chalk and blackboard used by men in
technical discussion.

1) Desk-Surface Display and Control: Certainly, for effective
man-computer interaction, it will be necessary for the man and the
computer to draw graphs and pictures and to write notes and equations
to each other on the same display surface. The man should be able to
present a function to the computer, in a rough but rapid fashion, by
drawing a graph. The computer should read the man's writing, perhaps
on the condition that it be in clear block capitals, and it should
immediately post, at the location of each hand-drawn symbol, the
corresponding character as interpreted and put into precise type-face.
With such an input-output device, the operator would quickly learn to
write or print in a manner legible to the machine. He could compose
instructions and subroutines, set them into proper format, and check
them over before introducing them finally into the computer's main
memory. He could even define new symbols, as Gilmore and Savell [14]
have done at the Lincoln Laboratory, and present them directly to the
computer. He could sketch out the format of a table roughly and let
the computer shape it up with precision. He could correct the
computer's data, instruct the machine via flow diagrams, and in
general interact with it very much as he would with another engineer,
except that the "other engineer"  would be a precise draftsman, a
lightning calculator, a mnemonic wizard, and many other valuable
partners all in one.

2) Computer-Posted Wall Display: In some technological systems,
several men share responsibility for controlling vehicles whose
behaviors interact.  Some information must be presented
simultaneously to all the men, preferably on a common grid, to
coordinate their actions. Other information is of relevance only to
one or two operators. There would be only a confusion of
uninterpretable clutter if all the information were presented on one
display to all of them. The information must be posted by a computer,
since manual plotting is too slow to keep it up to date.

The problem just outlined is even now a critical one, and it seems
certain to become more and more critical as time goes by. Several
designers are convinced that displays with the desired characteristics
can be constructed with the aid of flashing lights and time-sharing
viewing screens based on the light-valve principle.

The large display should be supplemented, according to most of those
who have thought about the problem, by individual display-control
units.  The latter would permit the operators to modify the wall
display without leaving their locations. For some purposes, it would
be desirable for the operators to be able to communicate with the
computer through the supplementary displays and perhaps even through
the wall display. At least one scheme for providing such communication
seems feasible.

The large wall display and its associated system are relevant, of
course, to symbiotic cooperation between a computer and a team of men.
Laboratory experiments have indicated repeatedly that informal,
parallel arrangements of operators, coordinating their activities
through reference to a large situation display, have important
advantages over the arrangement, more widely used, that locates the
operators at individual consoles and attempts to correlate their
actions through the agency of a computer. This is one of several
operator-team problems in need of careful study.

3) Automatic Speech Production and Recognition: How desirable and how
feasible is speech communication between human operators and
computing machines? That compound question is asked whenever
sophisticated data-processing systems are discussed. Engineers who
work and live with computers take a conservative attitude toward the
desirability. Engineers who have had experience in the field of
automatic speech recognition take a conservative attitude toward the
feasibility. Yet there is continuing interest in the idea of talking
with computing machines. In large part, the interest stems from
realization that one can hardly take a military commander or a
corporation president away from his work to teach him to type. If
computing machines are ever to be used directly by top-level decision
makers, it may be worthwhile to provide communication via the most
natural means, even at considerable cost.  Preliminary analysis of his
problems and time scales suggests that a corporation president would
be interested in a symbiotic association with a computer only as an
avocation. Business situations usually move slowly enough that there
is time for briefings and conferences. It seems reasonable, therefore,
for computer specialists to be the ones who interact directly with
computers in business offices.

The military commander, on the other hand, faces a greater probability
of having to make critical decisions in short intervals of time. It is
easy to overdramatize the notion of the ten-minute war, but it would
be dangerous to count on having more than ten minutes in which to make
a critical decision.  As military system ground environments and
control centers grow in capability and complexity, therefore, a real
requirement for automatic speech production and recognition in
computers seems likely to develop.  Certainly, if the equipment were
already developed, reliable, and available, it would be used.

In so far as feasibility is concerned, speech production poses less
severe problems of a technical nature than does automatic recognition
of speech sounds. A commercial electronic digital voltmeter now reads
aloud its indications, digit by digit. For eight or ten years, at the
Bell Telephone Laboratories, the Royal Institute of Technology
(Stockholm), the Signals Research and Development Establishment
(Christchurch), the Haskins Laboratory, and the Massachusetts
Institute of Technology, Dunn [6], Fant [7], Lawrence [15], Cooper
[3], Stevens [26], and their co-workers, have demonstrated successive
generations of intelligible automatic talkers. Recent work at the
Haskins Laboratory has led to the development of a digital code,
suitable for use by computing machines, that makes an automatic voice
utter intelligible connected discourse [16].

The feasibility of automatic speech recognition depends heavily upon
the size of the vocabulary of words to be recognized and upon the
diversity of talkers and accents with which it must work. Ninety-eight
per cent correct recognition of naturally spoken decimal digits was
demonstrated several years ago at the Bell Telephone Laboratories and
at the Lincoln Laboratory [4], [9]. Togo a step up the scale of
vocabulary size, we may say that an automatic recognizer of clearly
spoken alpha-numerical characters can almost surely be developed now
on the basis of existing knowledge. Since untrained operators can read
at least as rapidly as trained ones can type, such a device would be a
convenient tool in almost any computer installation.

For real-time interaction on a truly symbiotic level, however, a
vocabulary of about 2000 words, e. g., 1000 words of something like
basic English and 1000 technical terms, would probably be required.
That constitutes a challenging problem. In the consensus of
acousticians and linguists, construction of a recognizer of 2000 words
cannot be accomplished now. However, there are several organizations
that would happily undertake to develop an automatic recognize for
such a vocabulary on a five-year basis. They would stipulate that the
speech be clear speech, dictation style, without unusual accent.

Although detailed discussion of techniques of automatic speech
recognition is beyond the present scope, it is fitting to note that
computing machines are playing a dominant role in the development of
automatic speech recognizers.  They have contributed the impetus that
accounts for the present optimism, or rather for the optimism
presently found in some quarters.  Two or three years ago, it appeared
that automatic recognition of sizeable vocabularies would not be
achieved for ten or fifteen years; that it would have to await much
further, gradual accumulation of knowledge of acoustic, phonetic,
linguistic, and psychological processes in speech communication.  
Now, however, many see a prospect of accelerating the acquisition of
that knowledge with the aid of computer processing of speech signals,
and not a few workers have the feeling that sophisticated computer
programs will be able to perform well as speech-pattern recognizes
even without the aid of much substantive knowledge of speech signals
and processes. Putting those two considerations together brings the
estimate of the time required to achieve practically significant
speech recognition down to perhaps five years, the five years just
mentioned.
--------------

References 

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[3] F. S. Cooper, et al., "Some experiments on the perception of
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[4] K. H. Davis, R. Biddulph, and S. Balashek, "Automatic recognition
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[5] G. P. Dinneen, "Programming pattern recognition," Proc. WJCC, pp.  
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[6] H. K. Dunn, "The calculation of vowel resonances, and an
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[7] G. Fant, "On the Acoustics of Speech," paper presented at the Third 
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[9] J. W. Forgie and C. D. Forgie, "Results obtained from a vowel
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[10] E. Fredkin, "Trie memory," Communications of the ACM, Sept. 1960,
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[11] R. M. Friedberg, "A learning machine: Part I," IBM J. Res. &
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[12] H. Gelernter, "Realization of a Geometry Theorem Proving
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[14] J. T. Gilmore and R. E. Savell, "The Lincoln Writer," Lincoln
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[15] W. Lawrence, et al., "Methods and Purposes of Speech Synthesis,"  
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[16] A. M. Liberman, F. Ingemann, L. Lisker, P. Delattre, and F. S.
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[17] A. Newell, "The chess machine: an example of dealing with a
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[18] A. Newell and J. C. Shaw, 'Programming the logic theory machine."  
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[19] A. Newell, J. C. Shaw, and H. A. Simon, "Chess-playing programs
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[21] J. D. North, "The rational behavior of mechanically extended
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[23] C. E. Shannon, "Programming a computer for playing chess," Phil.  
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[24] J. C. Shaw, A. Newell, H. A. Simon, and T. O. Ellis, "A command
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[25] H. Sherman, "A Quasi-Topological Method for Recognition of Line
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[26] K. N. Stevens, S. Kasowski, and C. G. Fant, "Electric analog of
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*Copyright IRE (now IEEE), 1960, IRE Transactions on Human Factors in 
Electronics, volume HFE-1, pages 4-11, March 1960.
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