Methodology for generating enhanced demiphone acoustic models for speech recognition

A system for implementing a speech recognition engine, comprising:

• demiphone acoustic models that said speech recognition engine utilizes to perform speech recognition procedures, said demiphone acoustic models each having three states that collectively form a preceding demiphone and a succeeding demiphone;
• and
• an acoustic model generator that analyzes speech context information to configure each of said demiphone acoustic models as either a succeeding-dominant demiphone acoustic model or a preceding-dominant demiphone acoustic model, said speech context information being identified by decision trees that each include a series of questions, said questions each corresponding to a different acoustic speech characteristic, said questions each also being used to identify a contextual dominance characteristic corresponding to said different acoustic speech characteristic.

A method for implementing a speech recognition engine, comprising:

• utilizing demiphone acoustic models to perform speech recognition procedures, each of said demiphone acoustic models having three states that collectively form a preceding demiphone and a succeeding demiphone;
• and
• analyzing speech context information with an acoustic model generator to configure each of said demiphone acoustic models as either a succeeding-dominant demiphone acoustic model or a preceding-dominant demiphone acoustic model, a contextual dominance for each demiphone state from a given one of said demiphone acoustic models being determined by analyzing predominant contextual information in a triphone decision tree corresponding to said each demiphone state.

A method for implementing a speech recognition engine, comprising:

• utilizing demiphone acoustic models to perform speech recognition procedures, each of said demiphone acoustic models having three states that collectively form a preceding demiphone and a succeeding demiphone;
• and
• analyzing speech context information with an acoustic model generator to configure each of said demiphone acoustic models as either a succeeding-dominant demiphone acoustic model or a preceding-dominant demiphone acoustic model, said speech context information being identified by decision trees that each include a series of questions, said questions each corresponding to a different acoustic speech characteristic, said questions each also being used to identify a contextual dominance characteristic corresponding to said different acoustic speech characteristic.