Abstract: A method and apparatus for performing analysis on data collected at a point of sale is disclosed. The data from the point of sale is collected using voice recognition technique implemented on a mobile communication device. In order to enable this, a limited vocabulary word recognition technique is implemented using a set of libraries storing speech utterances in a memory storage unit present of the mobile communication device. Dynamic updating of module parameters associated with the stored speech utterances is enabled by a speech refinement unit of the mobile communication device. The device further enables local as well as regional data collation and analysis.

Abstract: System(s) and method(s) for classifying noise data of human crowd are disclosed. Noise data is captured from one or more sources and features are extracted by using computation techniques. The features comprise spectral domain features and time domain features. Classification models are developed by using each of the spectral domain features and the time domain features. Discriminative information with respect to the noise data is extracted by using the classification models. A performance matrix is computed for each of the classification model. The performance matrix comprises classified noise elements with respect to the noise data. Each classified noise element is associated with a classification performance score with respect to a spectral domain feature, a time domain feature, and fusion of features and scores. The classified noise elements provide the classification of the noise data.

Abstract: System(s) and method(s) for classifying noise data of human crowd are disclosed. Noise data is captured from one or more sources and features are extracted by using computation techniques. The features comprise spectral domain features and time domain features. Classification models are developed by using each of the spectral domain features and the time domain features. Discriminative information with respect to the noise data is extracted by using the classification models. A performance matrix is computed for each of the classification model. The performance matrix comprises classified noise elements with respect to the noise data. Each classified noise element is associated with a classification performance score with respect to a spectral domain feature, a time domain feature, and fusion of features and scores. The classified noise elements provide the classification of the noise data.

Abstract: A method and apparatus for performing analysis on data collected at a point of sale is disclosed. The data from the point of sale is collected using voice recognition technique implemented on a mobile communication device. In order to enable this, a limited vocabulary word recognition technique is implemented using a set of libraries storing speech utterances in a memory storage unit present of the mobile communication device. Dynamic updating of module parameters associated with the stored speech utterances is enabled by a speech refinement unit of the mobile communication device. The device further enables local as well as regional data collation and analysis.