1. A method comprising; obtaining access to a large reference acoustic model for automatic speech recognition, said large reference acoustic model having L states modeled by L mixture models, said large reference acoustic model having N components; identifying a desired number of components N c , less than N, to be used in a restructured acoustic model derived from said reference acoustic model, said desired number of components N c being selected based on a computing environment in which said restructured acoustic model is to be deployed, said restructured acoustic model also having L states; for each given one of said L mixture models in said reference acoustic model, building a merge sequence which records, for a given cost function, sequential mergers of pairs of said components associated with said given one of said mixture models; assigning a portion of said N c components to each of said L states in said restructured acoustic model; and building said restructured acoustic model by, for each given one of said L states in said restructured acoustic model, applying said merge sequence to a corresponding one of said L mixture models in said reference acoustic model until said portion of said N c components assigned to said given one of said L states is achieved.