Patent ID: 7930178

Claim:
A method comprising: converting frames of a speech signal into the spectral domain to identify feature vectors each comprising a plurality of frequency components; removing a D.C. frequency component from the plurality of frequency components to form a plurality of filtered frequency components; determining an energy value for the filtered frequency components for each frame; for each frame, dividing the plurality of filtered frequency components of the feature vector for the frame by the energy value for the filtered frequency components for the frame to form an energy-normalized feature vector comprising energy-normalized frequency components for the frame; and a processor constructing a model from the energy-normalized feature vectors, wherein constructing the model comprises: clustering frames of energy-normalized frequency components into mixture components by determining a distance d({tilde over (X)} i , {tilde over (X)} j ) between an energy-normalized feature vector {tilde over (X)} i for a frame i and an energy-normalized feature vector {tilde over (X)} j for a frame j as: d ⁡ ( X ~ i , X ~ j ) = ∑ f = 1 N / 2 ⁢ ( log ❘ X if ❘ - log ❘ X if ❘ ) 2 , where N is a number of samples of the speech signal in each frame used to convert the speech signal into the spectral domain, |X if | is the fth energy-normalized frequency component for energy-normalized feature vector and {tilde over (X)} i and |X if | is the fth energy-normalized frequency component for energy-normalized feature vector {tilde over (X)} j ; and forming separate model parameters for each mixture component.