System and method for generating heterogeneously tied gaussian mixture models for automatic speech recognition acoustic models

A method of generating an acoustic model, comprising:

• employing a first tying structure to tie weighted Gaussian distributions in a first pool to a first group of phones;
• and
• employing a second tying structure to tie weighted Gaussian distributions in a second pool to a second group of phones, said first tying structure differing from said second tying structure, said weighted Gaussian distributions in said first pool being mutually exclusive of said weighted Gaussian distributions in said second pool, at least a criterion distinguishing said first group of phones from said second group of phones.

A heterogeneously tied mixture (HTM) acoustic model, comprising:

• a first tying structure that ties weighted Gaussian distributions in a first pool to a first group of phones;
• and
• a second tying structure that ties weighted Gaussian distributions in a second pool to a second group of phones, said first tying structure differing from said second tying structure, said weighted Gaussian distributions in said first pool being mutually exclusive of said weighted Gaussian distributions in said second pool, at least a criterion distinguishing said first group of phones from said second group of phones.