1. Make a series of d-vector-based experiments.(testing on sentence 2 and 7)
1). Comparison experiments on "Input data", including one text / two texts / 15 texts.
2). Comparison experiments on different hidden layers, last-hid-layer with sigmoid normalization and without sigmoid normalization.
The experimental results are that:(compared by the value of EER(%))
1). two texts < 15 texts < one text (especially under the LDA condition); The d-vector can be used in sudo speaker recognition.
2). last-hid-layer without sigmoid normalization < last-hid-layer with sigmoid normalization. (under the LDA condition and no matter which input data).
2. To train a text-content-based neural networks and extract d-vectors from this network.
1. Go on the task1 and task2.