Abstract: A recognition apparatus 100 for ear acoustic recognition include a feature normalizer 101 which reads input ear acoustic data and removes the earphone's resonance effect from the input ear acoustic data to produce a normalized data at the output, a feature extractor 102 which extracts acoustic features from the normalized data, a classifier 103 which reads the acoustic features as input and classifies them into their corresponding class.

Abstract: An apparatus for pattern recognition includes a generator which transforms noisy feature vectors into denoised feature vectors, a discriminator which takes the denoised feature vectors and the original clean feature vectors corresponding to the denoised feature vectors as input and predicts probability for both of the input features of being an original clean feature, classifies the input feature vectors into its corresponding classes, an objective function calculator which calculates generator and discriminator losses using the denoised feature vectors, the clean feature vectors from which the noisy feature vectors have been made, the estimated classes and their true classes, and a Parameter updater which updates parameters of the generator and the discriminator according to loss minimization.

Abstract: A pattern recognition apparatus according to the present invention includes: a memory; and at least one processor coupled to the memory, the processor performing operations, the operations comprising: transforming noisy feature vectors into denoised feature vectors; classifying the denoised feature vectors into related classes and estimated classes; calculating a cost by using the denoised feature vectors, clean feature vectors, the estimated classes, and feature vector labels; and updating parameters for transforming the noisy feature vectors according to the cost.