Exploring Robustness of DNN/RNN for Extracting Speaker Baum-Welch Statistics in Mismatched Conditions
文献类型：会议论文
| 作者 | Hao Zheng ; Shanshan Zhang; Wenju Liu
|
| 出版日期 | 2015 |
| 会议日期 | 2015 |
| 会议地点 | Dresden, Germany |
| 关键词 | Dnn Rnn Speaker Recognition Mismatched Condition |
| 英文摘要 | This work explores the use of DNN/RNN for extracting Baum-Welch sufficient statistics in place of the conventional GMM-UBM in speaker recognition. In this framework, the DNN/RNN is trained for automatic speech recognition (ASR) and each of the output unit corresponds to a component of GMM-UBM. Then the outputs of network are combined with acoustic features to calculate sufficient statistics for speaker recognition. We evaluate and analyze the performance of networks with different configurations and training corpuses in this paper. Experimental results on text-independent SRE NIST 2008 and text-dependent RSR2015 speaker verification tasks show the robustness of DNN/RNN for extracting statistics in mismatched evaluation conditions compared with GMM-UBM system. Particularly, Long Short-Term Memory (LSTM) RNN realized in this work outperforms traditional DNN and GMM-UBM in most mismatched conditions. |
| 会议录 | INTERSPEECH
 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/11780]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_机器人视觉团队 |
| 通讯作者 | Hao Zheng |
| 作者单位 | National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences |
| 推荐引用方式 GB/T 7714 | Hao Zheng,Shanshan Zhang,Wenju Liu. Exploring Robustness of DNN/RNN for Extracting Speaker Baum-Welch Statistics in Mismatched Conditions[C]. 见:. Dresden, Germany. 2015. |
入库方式： OAI收割
来源：自动化研究所
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