Language Identification with Deep Bottleneck Features

时间 2020-12-23

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时间：2018.9 没看到发布的地址作者：Zhanyu Ma, Hong Yu abstract 用于中文音素分类的DNN的bottleneck特征被用于LSTM的训练。 1. introduction SLD任务用在语音识别的前端，首先判别一句话的语种，然后唤醒对应的decode去翻译成文本。世界上有上千种语言，每种语言有不同的区分特征，想要找到一种通用的，快速响应的有效SLD system

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1. 深度学习之Bottleneck Layer or Bottleneck Features
2. BN for Language Identification
3. Learning Transferable Features with Deep Adaptation Networks
4. Large-Scale and Language-Oblivious Code Authorship Identification
5. 【Person Re-ID】Deep-Person: Learning Discriminative Deep Features for Person Re-Identification
6. [c++] C Language Features
7. 【ReID】Learning Discriminative Features with Multiple Granularities for Person Re-identification
8. 翻译“Learning Transferable Features with Deep Adaptation Networks”
9. Content-based image retrieval with compact deep convolutional features
10. Deep Reinforcement Learning with a Natural Language Action Space

>>更多相关文章<<