response to the one or more data record(s) associated with subscriber 120, controls messaging controller 210.
Tu, illustrated is a conceptual configuration of a conventional memory 400 that includes data repository 200. Data repository 200 includes a plurality of data patterns 405 (i.e., speech models constructed using
knowledge of acoustics, language, dictionaries, grammars or the like) and a plurality of subscriber records 410.
According to this embodiment, a particular subscriber Gmail Numeric Code 6922 issue record 415 is associated with subscriber 120 and, among its other attributes, includes pointers to particular ones of the plurality of data patterns 405. These particular data
patterns are a “subset” of data patterns that represent oral phrases common to subscriber 120. Thus, while data patterns 405 are collectively specific to a general type of non-realtime messaging system, namely, message paging system
100, this subset of data patterns is particularly related to subscriber 120.
Referring back to the above-given example, assume again that a freight delivery company subscribes to a suitably arranged message paging system and each of its drivers carries a conventional alphanumeric message pager. Assume further
that one of its drivers is subscriber 120 and that subscriber 120 works directly for “Joe,” is married to “Jane,” delivers a lot of “widgets,” and his primary delivery stops are at “ABC Company,” “XYZ Inc.,” and “OPQ Limited.” Data
record 415 may suitably define a data pattern subset of {joe jane widgets abc co. company xyz inc. incorporated opq ltd. limited}. Data patterns 405, used in combination with a suitable subset thereof, may cooperatively provide a
context sensitive vocabulary that can increase the likelihood that translating controller 205 will successfully translate (recognize, at least in part) a received oral message, but can also decrease the time required to translate the
same.
As above-discussed with reference to APPENDIX A, data patterns 405 may be static or dynamic. Similarly, the subset of data patterns may also be static or dynamic. The subset may be defined once, periodically, etc., or it may be defined
and redefined in response to the frequency with which various ones of data patterns 405 are used. For instance, system 100 may determine that subscriber 120 is regularly stopping at “DEF Co.” and modify the above-identified subset
associated with subscriber 120 accordingly. Alternatively, assume subscriber 120 is injured and placed on disability leave. Assume further that the regular stops assigned to subscriber 120 are reassigned to another driver. Under this
scenario, system 100 may associate the data pattern subset associated with subscriber 120 with that of this second driver.
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