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A simple model implemented with tensorflow for voiceprint

wav-->fbank-->lstm-->embedding-->train and test/softmax(pretrain)-->train

dataset: https://datashare.is.ed.ac.uk/download/DS_10283_2651.zip

Hyperparameters used in the model

• duration of wavs used for training: 2000ms
• how long each frame of spectrograme: 25ms
• how far to move in time between two frames: 10ms
• numbers of coefficients of fbank: 40
• numbers of enrollment utts for each speaker: 5
• numbers of units for each layer of lstm: 128
• dimension of projection layer of lstm: 64
• number of layers of multi-lstm: 3
• dimension of linear layer on top of lstm: 64
• learning rate: 0.0001
• dropout prob: 0.5
• batch size: 80
• Each batch contains N = 8 speakers and M = 10 utterances per speaker.
• Each batch contains N = 64 speakers and M = 10 utterances per speaker.