speakerIdentificationNeuralNetworks
β¨ The Speaker Recognition System consists of two phases, Feature Extraction and Recognition. β¨ In the Extraction phase, the Speaker's voice is recorded and typical number of features are extracted to form a model. β¨ During the Recognition phase, a speech sample is compared against a previously created voice print stored in the database. β¨ The highlight of the system is that it can identify the Speaker's voice in a Multi-Speaker Environment too. Multi-layer Perceptron (MLP) Neural Network based on error back propagation training algorithm was used to train and test the system. β¨ The system response time was 74 Β΅s with an average efficiency of 95%.
