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manthanthakker / speakerIdentificationNeuralNetworks

⇨ The Speaker Recognition System consists of two phases, Feature Extraction and Recognition. ⇨ In the Extraction phase, the Speaker's voice is recorded and typical number of features are extracted to form a model. ⇨ During the Recognition phase, a speech sample is compared against a previously created voice print stored in the database. ⇨ 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. ⇨ The system response time was 74 µs with an average efficiency of 95%.

Repository from Github https://github.commanthanthakker/speakerIdentificationNeuralNetworksRepository from Github https://github.commanthanthakker/speakerIdentificationNeuralNetworks

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