“150308-Lantian Li”版本间的差异
（以“Weekly Summary 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 te...”为内容创建页面） |
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| 第13行： | 第13行： | ||
2). last-hid-layer without sigmoid normalization < last-hid-layer with sigmoid normalization. (under the LDA condition and no matter which input data). | 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 | + | 2. To train a text-content-based neural networks and extract d-vectors from these networks. |
Next Week | Next Week | ||
1. Go on the task1 and task2. | 1. Go on the task1 and task2. | ||
2015年3月9日 (一) 14:13的最后版本
Weekly Summary
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 these networks.
Next Week
1. Go on the task1 and task2.
