14. A method of language independent speech recognition comprising: a. receiving input speech with a speech pre-processor and producing a speech-related signal representative of the input speech; b. representing in a database of acoustic hidden Markov models, subword units in each of a plurality of languages, wherein any subword unit that is common to two or more of the plurality of languages is represented by a single common acoustic hidden Markov model; c. characterizing in a language model a vocabulary of recognizable words and a set of grammar rules; and d. comparing in a speech recognizer the speech-related signal to the acoustic hidden Markov models and the language model, and recognizing the input speech as a specific word sequence of at least one word.
14. A method of language independent speech recognition comprising: a. receiving input speech with a speech pre-processor and producing a speech-related signal representative of the input speech; b. representing in a database of acoustic hidden Markov models, subword units in each of a plurality of languages, wherein any subword unit that is common to two or more of the plurality of languages is represented by a single common acoustic hidden Markov model; c. characterizing in a language model a vocabulary of recognizable words and a set of grammar rules; and d. comparing in a speech recognizer the speech-related signal to the acoustic hidden Markov models and the language model, and recognizing the input speech as a specific word sequence of at least one word. 18. A method according to claim 14, wherein the subword units are at least one of phonemes, parts of phonemes, and sequences of phonemes.