Method, apparatus, mobile terminal and computer program product for providing efficient evaluation of feature transformation
AssigneeNokia Corporation
InventorsJilei Tian, Jani K. Nurminen, Victor Popa
Life of this patent
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Abstract
An apparatus for providing efficient evaluation of feature transformation includes a training module and a transformation module. The training module is configured to train a Gaussian mixture model (GMM) using training source data and training target data. The transformation module is in communication with the training module. The transformation module is configured to produce a conversion function in response to the training of the GMM. The training module is further configured to determine a quality of the conversion function prior to use of the conversion function by calculating a trace measurement of the GMM.
Claims36
A method comprising:
- training a Gaussian mixture model (GMM) using training source data and training target data;
- producing a conversion function in response to the training;
- determining a quality of the conversion function prior to use of the conversion function by calculating a trace measurement of the GMM;
- and
- selectively using the conversion function for feature transformation based on the trace measurement.
A computer program product comprising at least one computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising:
- a first executable portion for training a Gaussian mixture model (GMM) using training source data and training target data;
- a second executable portion for producing a conversion function in response to the training;
- a third executable portion for determining a quality of the conversion function prior to use of the conversion function by calculating a trace measurement of the GMM;
- and
- a fourth executable portion for selectively using the conversion function for feature transformation based on the trace measurement.
An apparatus comprising a processor configured to control:
- a training module configured to train a Gaussian mixture model (GMM) using training source data and training target data;
- and
- a transformation module in communication with the training module, the transformation module being configured to produce a conversion function in response to the training of the GMM,
- wherein the training module is further configured to determine a quality of the conversion function prior to use of the conversion function by calculating a trace measurement of the GMM.
A mobile terminal comprising a processor configured to control:
- a training module configured to train a Gaussian mixture model (GMM) using training source data and training target data;
- and
- a transformation module in communication with the training module, the transformation module being configured to produce a conversion function in response to the training of the GMM and thereafter, convert source data input into target data output using the GMM,
- wherein the training module is further configured to determine a quality of the conversion function prior to use of the conversion function by calculating a trace measurement of the GMM, and wherein the processor is configured to selectively use the conversion function for feature transformation based on the trace measurement.
An apparatus comprising:
- a means for training a Gaussian mixture model (GMM) using training source data and training target data;
- a means for producing a conversion function in response to the training;
- and
- a means for determining a quality of the conversion function prior to use of the conversion function by calculating a trace measurement of the GMM;
- and
- means for selectively using the conversion function for feature transformation based on the trace measurement.
An apparatus comprising a processor configured to:
- train a Gaussian mixture model (GMM) using training source data and training target data;
- produce a conversion function in response to the training;
- determine a quality of the conversion function prior to use of the conversion function by calculating a trace measurement of the GMM;
- and
- selectively use the conversion function for feature transformation based on the trace measurement.
Dependencies are inferred from the claim text.