17. A method for recognizing individual words of speech independent of the speaker thereof from a vocabulary consisting of a limited number of words, said method comprising the steps of: establishing a data base from a population of different speakers uttering the same list of a limited number of individual words to be included in the vocabulary for which speaker-independent word recognition is to be applicable; determining a sequence of time-ordered acoustic events based upon a zero-crossing rate and an energy measurement as the sole speech parameters corresponding to each word for each of the different speakers whose utterances are included in the data base; assigning a probability distribution function of each acoustic event included in each of the sequences of time-ordered acoustic events corresponding to respective individual words to be included in the vocabulary based upon the statistical averages obtained from the data base of the population of different speakers; representing a plurality of probabilistic acoustic events based upon the probability distribution function of a given acoustic event included in the sequence of acoustic events corresponding to an individual word as a reference vector such that each of the probabilistic acoustic events is based upon the relative likelihood of occurrence of an acoustic event therein; arranging a set of a plurality of reference vectors in a sequence comprising an acoustic description of an individual word; generating a reference template of digital speech data representative of an individual word from each set of reference vectors; measuring an input analog speech signal by substantially simultaneously obtaining energy measurements of said input analog speech signal and sensing zero-crossings of said input analog speech signal to provide word-discrimination information as a sequence of feature vectors, each of which is based solely upon an energy measurement and a zero-crossing rate and defines an acoustic event; extracting said sequence of feature vectors; comparing each feature vector of said input analog speech signal as extracted with the corresponding reference vectors of each of a plurality of said reference templates of digital speech data respectively representative of individual words comprising the vocabulary of the limited number of words; determining a distance measure with respect to the corresponding reference vectors in the predetermined sequences defining acoustic descriptions of the respective words for each feature vector of said input analog speech signal as a result of the comparisons therebetween; and recognizing a word as represented by the input analog speech signal on the basis of determining which one of said plurality of reference templates is the closest match to the input analog speech signal based upon a cumulative cost profile as defined by the respective distance measures provided by the comparison of each feature vector of said input analog speech signal with the reference vectors included in predetermined sequences of reference vectors defining said plurality of reference templates.
19. A method for recognizing a word as set forth in claim 17, further including developing word-pair associations in the vocabulary of the limited number of words as determined by sound similarities therebetween; and during the word-recognition determination, compensating for the bias caused by the tendency of one word in a given pair to be falsely recognized as the other word of the pair such that interpretation of the cumulative cost profile provided by the comparisons of each feature vector of said input analog speech signal with the corresponding reference vectors of each of said reference templates is improved in selecting the correct word of the given word-pair as represented by the input analog speech signal.