-8) do not substantially match the spectral model (1-6), the analyzed speech is not recognized. If a reference model (1-8) substantially matches the spectrally analyzed input speech (1-6), the words are determined or considered to be matched. The closeness of the representation match will, of course, be a function of how fault tolerant the speech recognition needs to be and is a design choice.
Once a match between a reference model (1-8) and an input word (1-6) is determined to have been made, an output signal is produced indicating that the particular word that has been matched. The matched word is delivered to a post processor (1-10).
The invention described herein is a method for post-processing recognized speech.
The invention requires that every word to be recognized by the system, first be specified in advance. These specified words form a set of such words, which together can be used to express some input that must be acted upon. If a recognizable word is not a keyword within the list of such words, the system cannot and will not use such words in its processing.
By way of example, if the system shown in FIG. 2 were to be used by an airline for automatically accepting travel reservations without human intervention, the set of language keywords might be specified to include words such as: “domestic” “international” “first” “coach” “class” as well as the names of destination cities served by the airline, dates, days of the week, months of the year, and times of day. In actual use, a phone call to the airline by a customer received and processed by the invention 2-4 would cause the system to query the customer to specify what his or her travel plans were. An airline customer wishing to make reservations to fly to a particular destination city, on a particular day or date, would likely utter one or more of the aforementioned keywords. Detection and identification of a sufficient number of keywords eventually permits the system to render a decision as to the customer's intended statement. For example, consider the phrase: “I'd like to fly to Miami from Chicago at eight AM on Jan. 1, 1998, in first class.” Only the words necessary to make a reservation on the airline to one of its destinations is included in the system's vocabulary. This invention also provides for the treatment of incomplete utterances, and input ambiguity caused by homonyms or by input errors.
Once a determination is made that the input speech is understood, at least insofar as the system determines the meaning, a situational-coherent response 2-6 is preferably produced to let the customer or user know that his or her input speech has been understood and acted upon. For the example set forth above, the response from a speech synthesis module might be an oral confirmation that the customer's reservation has been accepted, flight arrangements are played back to him, and a reservation confirmation number has been created and enunciated to the caller.
The present invention overcomes a limitation that is currently inherent in all computer-based speech processing systems. Because of finite computational resources, and finite memory capabilities, the present system as well as all prior art systems, contemplate a limited vocabulary of recognizable words.
The recognizable words are determined in advance to have associative relationships between each other. The relationships between these words define for the system a language. The language is therefore a limited number of possible input strings of recognizable words. The invention herein, however, has a finite amount of intelligence by which it can recognize simple sentences formed from a limited number of words that are strung together in random order. Unlike prior art system, this system seeks to clarify incomplete or ambiguous inputs.
What the system does not attempt to recognize and in fact filters out, are certain words that carry no information or have little meaning such as prepositions in spoken text. Words that are not recognized are discarded and not processed. If an utterance is comprised of unrecog