Knowledge Commons of Institute of Automation,CAS
Boosting noise robustness of acoustic model via deep adversarial training | |
Liu, Bin1,2; Nie, Shuai1,2; Zhang, Yaping1,2; Ke, Dengfeng1,3; Liang, Shan1; Liu, Wenju1 | |
2018-04 | |
会议名称 | IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |
会议日期 | 2018-4-15 |
会议地点 | 加拿大卡尔加里 |
出版地 | 美国 |
出版者 | IEEE Xplore |
摘要 | In realistic environments, speech is usually interfered by various |
关键词 | Robust Speech Recognition Deep Adversarial Training Acoustic Model Generative Adversarial Net |
收录类别 | EI |
资助项目 | National Natural Science Foundation of China[91120303] ; National Natural Science Foundation of China[61273267] ; National Natural Science Foundation of China[61403370] ; National Natural Science Foundation of China[61503382] ; National Natural Science Foundation of China[61573357] ; National Natural Science Foundation of China[61573357] ; National Natural Science Foundation of China[61503382] ; National Natural Science Foundation of China[61403370] ; National Natural Science Foundation of China[61273267] ; National Natural Science Foundation of China[91120303] |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/38559 |
专题 | 多模态人工智能系统全国重点实验室_智能交互 |
作者单位 | 1.1National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China 2.2School of Artificial Intelligence, University of Chinese Academy of Sciences, China 3.School of Information Science and Technology, Beijing Forestry University, China |
第一作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Liu, Bin,Nie, Shuai,Zhang, Yaping,et al. Boosting noise robustness of acoustic model via deep adversarial training[C]. 美国:IEEE Xplore,2018. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
icassp2018.pdf(300KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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