3. The method of claim 2 wherein the multilingual dispatcher engine maintains and updates runtime states of language-specific pronunciations by executing the language-specific state initialization and state update components against the language-specific format of a current feature vector.
3. The method of claim 2 wherein the multilingual dispatcher engine maintains and updates runtime states of language-specific pronunciations by executing the language-specific state initialization and state update components against the language-specific format of a current feature vector. 4. The method of claim 3 wherein the multilingual dispatcher engine includes score scaling functions, which convert a hypothesis score from its language-specific scale to a multilingual dispatcher engine scale and from the multilingual dispatcher engine scale to a language-specific scale, these functions enabled as best-fit functions to generate equal multilingual dispatcher engine scores for silence and, optionally, noise hypotheses, in different languages on qualified application-dependent noise utterances.