DDC
| 621 |
Tác giả CN
| Quoc Bao Nguyen |
Nhan đề
| Improving Bottleneck Features For Vietnamese Large Vocabulary Continuous Speech Recognition System Using Deep Neural Networks / Quoc Bao Nguyen, Tat Thang Vu, Chi Mai Huong |
Mô tả vật lý
| 10 p. |
Tóm tắt
| In this paper, the pre-training method based on denoising auto-encoder is investigated and proved to be good models for initializing bottleneck networks of Vietnamese speech recognition system that result in better recognition performance compared to base bottleneck features reported previously. The experiments are carried out on the dataset |
Từ khóa tự do
| Neural network |
Từ khóa tự do
| Deep bottleneck features |
Từ khóa tự do
| Vietnmnese speech recognition |
Tác giả(bs) CN
| Chi Mai Huong |
Tác giả(bs) CN
| Tat Thang Vu |
Nguồn trích
| Tạp chí Tin học và Điều khiển học = Journal of Computer Science And Cybernetics 2015P. 267-276
Số: 31
Tập: 4 |
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082 | |a621 |
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100 | |aQuoc Bao Nguyen |
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245 | |aImproving Bottleneck Features For Vietnamese Large Vocabulary Continuous Speech Recognition System Using Deep Neural Networks / |cQuoc Bao Nguyen, Tat Thang Vu, Chi Mai Huong |
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300 | |a10 p. |
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520 | |aIn this paper, the pre-training method based on denoising auto-encoder is investigated and proved to be good models for initializing bottleneck networks of Vietnamese speech recognition system that result in better recognition performance compared to base bottleneck features reported previously. The experiments are carried out on the dataset |
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653 | |aNeural network |
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653 | |aDeep bottleneck features |
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653 | |aVietnmnese speech recognition |
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700 | |aChi Mai Huong |
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700 | |aTat Thang Vu |
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773 | |tTạp chí Tin học và Điều khiển học = Journal of Computer Science And Cybernetics |d2015|gP. 267-276|v4|i31 |
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890 | |c1|a0|b0|d7 |
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