Speech2Phone: A Multilingual and Text Independent Speaker Identification Model
Table 2: Open-set Hyperparameters
['Model', 'Epochs', 'Learning Rate', 'Batch Size']
Model 4 will be referred as Speech2Phone and consists of a dense neural network with one hidden layer. Model 5 is combined with model 4, while the latter generates embeddings, the former analyzes a pair of embeddings to indicate if they belong to the same speaker. KNN is an alternative to Model 5 to find the most similar embedding of a speaker. Model 6 combines convolution dense layers to generate the output. Model 7 is inspired by Convolutional Autoencoders, also know as Fullly Convolutional Networks, and, therefore uses only convolutional layers. Model 8 explores recurrent networks. Finally, Model 9 combines recurrent and convolutional layers.