saaalz's repositories
Blue-topaz-example
Blue topaz themes example vault for Obsidian
machine_learning
the implimentation of machin learning
Recurrent_Autoencoder
Recurrent autoencoder for time-series analysis [Tensorflow]
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%.