text: the main components of a system according to the present invention are illustrated in fig1 . overall operation is controlled by dialogue control means 1 according to an application - specific dialogue specification the function of which is to exchange information with a user and access , update , or otherwise exercise control over an object system 3 . user interaction consists of a sequence of question / answer cycles where each question is designed to elicit some specific information . output is generated by means of a generator , in this example a speech output generator . the response of the user is processed by the input device 4 , in this example , a speech recogniser . based upon any input the dialogue control means 1 updates its internal control state and determines the next action of the system . this continues until the information need of the user is satisfied and the interactive operation is terminated . an alternative scheme , for which this system is equally applicable , is where the overall control is vested with the target system 3 , and this calls on the dialogue control means 1 to invoke a particular sub - dialogue specified by 2 . the dialogue control means 1 employs augmented transition networks specified in the specification 2 to control the operation of the system . fig2 shows an example of such a network , which represents a simple sub - dialogue , the function of which is to obtain a date from a user . basically , it consists of a set of states 10 linked together by directional transitions 11 . the states 10 represent a system action , such as a question / answer cycle , data processing , a simple junction , or a sub - dialogue state , which expands to another similar network . the transitions 11 , and their associated conditions , determine the course of dialogue flow after a particular state 10 has been reached and executed . a similar network is also used in the system in order to provide syntactic constraints for speech input . in this case , grammatical rules may be expressed in the form of finite state networks , such as the “ date ” network shown in fig3 . again , there are states 10 and transitions 11 , but in this case the states represent an acoustic phenomenon such as a word , to be matched with incoming speech data , or , as before , sub - networks or simple junctions . speech output is typically derived from a simple text string which can translated by the speech output device 5 into speech . this can be done by using a simple , well known , text - to - speech algorithm , or by joining together previously recorded acoustic wave forms . in the current system this is preferably treated as a very simple network with a single permissible path , and with each output word representing a state 10 . employment of the above structure means that all states , whether associated with speech output , speech input , or overall dialogue control , can be associated with an action or actions 12 , each of which is a simple procedural form specified by the system designer . this , in turn , allows the provision of action which receives , modifies , and then forwards , a token . the token is an object which contains information embodying the current state of knowledge of the system , and a link to its predecessor , from which the history of the dialogue up to the point of the action in question can be obtained . the token should consist in part of a set of fields that are known and modifiable by the previously defined control means 1 , input device 4 and output device 5 , and which are also accessible to the application - specific actions 12 and transition conditions 11 . for example , recognition and confidence corresponding to speech input , or the count of the number of times that a dialogue state has been traversed . in addition the token has a further set of fields which may be specified by a system designer , known and modifiable by the application specific actions attached to the states 10 and transition conditions 11 . the token is arranged to be propagated according to the transitions in the network in the system and is copied to state actions . copying varies upon the context of the state action . for example , in the case of dialogue , propagation occurs as and when states are encountered ( as dictated by transition conditions ), based on token fields . when the dialogue system is embedded within another application , as can be the case with this system , the token is passed by the calling application to the entry state of the sub - dialogue and copied back from the exit state on completion of the dialogue . for the states which require a user interaction the token is copied to the initial state of the speech output . for speech output , copying occurs synchronously with the speech output itself , but a token exiting any speech output state is also transmitted to the start of the speech recognition network . in the case of speech input , each token is copied time - synchronously for each incoming token and for each hypothesis ( i . e . for each alternative path through the input network ) as and when it is considered by the recogniser . during recognition , competing tokens arriving at the same state can be recombined according to a simple comparison of sets of fields nominated by a system designer . such fields may represent the semantics of a particular utterance . at the end of recognition , only the best scaring token is re - transmitted to the dialogue network following therefrom . the employment of tokens of the above type and the passage of them through the whole operation of the system , not solely from the speech recognition , speech output , or dialogue control , has considerable advantages . for example , unless complex systems are broken down into independent sub - components which interface in a well - defined way with the rest of the system , design of such systems is time consuming and complex . development time and complexity can be reduced , however , by developing and testing sub - components separately and then combining them . this is difficult to do , however , and still ensure that the interface definitions do not have to be restructured , making modularity difficult to achieve in practice . furthermore , dialogues are often implemented in such systems using conventional programming language variable scoping . this leads to much of the knowledge of a system being implemented as some form of global variable , as this is often the simplest way to make sure that all components of a dialogue have access to the appropriate knowledge . with this , however , modularity is lost , and sub - dialogues cannot straightforwardly be extracted from one system and plugged into another , as there will not be a consistent set of global variables . in addition , global variables , once updated , lose all information pertaining to previous settings , meaning that it is difficult to obtain back tracking information without explicit result saving , which can be complicated and error - prone . the arrangement of the present invention overcomes these problems . dialogue sub - components may specify an interface in terms of token fields which are intended for import / export to the rest of the system and may also maintain a set strictly local to the sub - components . all other fields are still transferred by the token , but invisibly to sub - components which do not explicitly import them . this means , for example , that extra , unelicited , information that may be supplied by a user in mixed initiative dialogues , such as the time of day in a response “ to edinburgh this evening ”, can be carried forward through the dialogue until a sub - component that recognises the extra information , in this case , a time , can be found . in addition , and most importantly , the system of the invention means that the current state of knowledge at all stages of the dialogue is known , given that the token is copied from state to state , and can therefore be regained as required . this is useful during debugging of a system in development , in backtracking during operation , and for the provision of a formal history mechanism , whereby the application designer can pose arbitrary questions concerning previous utterances in the history of the dialogue . there are additional features that can be provided in the system once the employment of tokens of the type described above is realised . a first example is the extraction of knowledge from recognition results . in prior art systems there is often a substantial post - processing phase , often involving sophisticated parsing techniques , which now becomes simple with the system and method of the present invention . in effect , this is because the parsing is now performed by the speech recogniser . in fig3 specific states have black triangle marks which indicate that they have a semantic action 12 attached . a typical action might be associated with a time sub - syntax state . before the action is taken , the system fills in the recognition and confidence fields of the associated token with an actual recognition , such as “ at half past 5 ”. in this example hour and minute have already been set during traversal of the time syntax , and the action simply records the time , and the confidence for the whole of the time utterance . the syntactic variant employed by the user ( that is “ at half past 5 ”, as opposed to “ 5 . 30 ”, “ 17 . 30 ”, etc ), is also recorded in this example , and this may then be used in the confirmation procedure . it is important to note that with the system of the invention the confidence of any selected part of the input can be obtained trivially , an advantage for the application designer in assessing the confidence with which the semantics of a user - utterance should be held , and also meaning that , when expedient , it is possible to restrict explicit confirmation only to those sections of the input which are uncertain . another example is the employment of dialogue knowledge to guide the recogniser . it is common for constraints on the recogniser to be syntactic , and to take the form of the grammatical rules of the language being recognised . unfortunately , in practice spoken dialogue is often not so closely tied with grammatical rules , and constraints must be loosened in order to accommodate a more natural dialogue style , reducing recognition accuracy . with the system of the present invention , however , additional semantic constraint can be employed . semantic constraints relate to the meaning of an utterance , and are rarely broken by well - motivated users . for example , a speaker is unlikely to say “ i wish to travel to london from london ”, “ february 31 ”, or to reply to a question such as “ do you want to leave on sunday morning ?” with “ no . i want to leave on sunday morning .”. typically , such constraints are non - context - free , and cannot be applied using conventional syntax networks without considerable inconvenience and difficulty . using the present method of invention , however , these sort of constraints can be applied strictly without compromising natural responses generated by the system . recognition can return a score which is then added by the system to the acoustic likelihoods employed in the recognition , which can simply turn paths on or off depending upon the semantics denoted by field defined by a system designer . fig5 shows a simple example of this for a confirmed date syntax , where a return value of zero means that a pass is unaffected by semantic constraint , and a return value of the infinity that the path is forbidden . related to the above is the employment of semantic classification statistics . in recent years significant advantages in speech recognition have been achieved by the application of statistics to the use of dialogue and to the order in which words are spoken , with the statistical probability adjusting the raw acoustic scores produced by the speech recogniser . for the “ date ” syntax shown in fig2 the employment of such a technique would involve the association of probabilities with the various paths 11 through the network , the probabilities corresponding to the frequency with which the path is selected and hence the frequency with which a particular syntactic form is selected by users in order to specify a date . similarly , if the user is permitted to enter several different items , date , times , place , etc , in one utterance , the order in which these items tend to be specified can be recorded as similar statistical processing applied . in practice , however , such processing is limited to relationships which can be expressed in terms of a conventional context - free grammar . in interactive dialogues , there is a common tendency for users to confirm information already supplied by repeating it within the same utterance or at a later stage in the dialogue . this tendency cannot be modelled by conventional context - free grammars , and so much statistical information is lost . with the method and system of the invention this problem can be solved . for example , consider the two responses : “ to london — to london from manchester ” and “ to london — to durham from manchester ”. syntactically they are identical consisting of two “ to place ” sub - syntaxes followed by “ from place ”, and would be assigned the same weight using conventional probabilistic syntactics . semantically , however , they are very different , the first representing a confirmation of a previous assertion , and the second a correction . fig5 shows how these cases can be distinguished by assigning different paths for each and then using collected data to assign probabilities to the path , in a simple conventional manner . the system and method of the present invention also enables the propagation of acoustic likelihoods . dialogues usually involve several interchanges between a user and a system . for each user utterance acoustic scores are available which support ( or reject ) the various hypotheses that the system might make about the user &# 39 ; s intentions , for example that the user wishes to travel to a certain place . these constitute independent pieces of evidence for or against an initial hypotheses and as such can be combined using bayesian statistics , so that the probability of a hypotheses becomes ever more certain ( or remote ) as the system proceeds from utterance to utterance . the system and method of the present invention can perform this simply by transferring appropriate information via the token or tokens passing through the system . prior art systems do not work so easily , however . for each utterance , recognition starts afresh , considering all earlier hypotheses as equally likely . an example of the advantages provided in relation to this is in relation to error correction . a dialogue can become very long and tedious if every piece of information must be explicitly confirmed . if such confirmation is not employed , however , the user must be able to correct selected items presented to them by the system . this means that syntax constraints must be very wide , leading to a high chance of false correction . with the present invention this problem disappears because the system can accumulate hypotheses , probabilities based on previous utterances and can use them to weight future recognition results . this in turn has benefits in that a number of irreversible decisions the system designer must make are in use . for example , because a hypotheses is supported by some high confidence level in the prior art the designer may be required to accept such hypotheses as true , but with the system and method of the present invention of course assumptions can also be rectified without compromising overall system ability . a yet further benefit of the present invention is that a consistent way is provided in which the system can be configured to employ other knowledge sources which might typically be used to assist recognition . humans use this extensively to aid understanding . for example a likelihood of a particular event can be improved with a travel or directory enquiry given the knowledge that a caller &# 39 ; s home city is more likely to be involved in the enquiry than any other city . other acoustic clues , such as prosody can also be employed . for example , if a user is confirming a set of correct digits , but puts emphasis on digits which are currently recognised wrongly it has considerable benefits if the system is able to access some measure of the emphasis applied . this can be arranged simply with the invention by employment of the tokens . a yet further example of the benefits of the present invention is the employment of “ barge - in ”. barge - in has became very popular in sds . users are allowed to interrupt system output , perhaps to contradict a false statement , or simply to anticipate the question . barge - in is , however , highly problematical . recognition is not so good , non - speech noises , such as coughing , can produce an unwanted interrupt , and responses are very difficult to understand without knowing quite precisely when , in relation to the output , the user interrupted the system . with the system and method of the present invention , by the explicit flow of tokens from output states to the start of the recognition network , these problems can ameliorated . different recognition syntaxes may be employed for interruptions , and explicit action may be taken to compensate for the increased unreliability of recognition in such the circumstances .