Auxiliary Loss Multimodal GRU Model in Audio-Visual Speech Recognition | |
Yuan, Yuan; Tian, Chunlin; Lu, Xiaoqiang1 | |
作者部门 | 光学影像学习与分析中心 |
2018 | |
发表期刊 | IEEE ACCESS |
ISSN | 2169-3536 |
卷号 | 6页码:5573-5583 |
产权排序 | 1 |
摘要 | Audio-visual speech recognition (AVSR) utilizes both audio and video modalities for the robust automatic speech recognition. Most deep neural network (DNN) has achieved promising performances in AVSR owing to its generalized and nonlinear mapping ability. However, these DNN models have two main disadvantages: 1) the first disadvantage is that most models alleviate the AVSR problems neglecting the fact that the frames are correlated; and 2) the second disadvantage is the feature learned by the mentioned models is not credible. This is because the joint representation learned by the fusion fails to consider the specific information of categories, and the discriminative information is sparse, while the noise, reverberation, irrelevant image objection, and background are redundancy. Aiming at relieving these disadvantages, we propose the auxiliary loss multimodal GRU (alm-GRU) model including three parts: feature extraction, data augmentation, and fusion & recognition. The feature extraction and data augmentation are a complete effective solution for the processing raw complete video and training, and precondition for later core part: fusion & recognition using alm-GRU equipped with a novel loss which is an end-to-end network combining both fusion and recognition, furthermore considering the modal and temporal information. The experiments show the superiority of our model and necessity of the data augmentation and generative component in the benchmark data sets.
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关键词 | Aduio-visual Systems Recurrent Neural Networks Generative Adversarial Networks |
DOI | 10.1109/ACCESS.2018.2796118 |
收录类别 | SCI ; EI |
语种 | 英语 |
WOS记录号 | WOS:000426304300001 |
EI入藏号 | 20180704784763 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.opt.ac.cn/handle/181661/30774 |
专题 | 光谱成像技术研究室 |
作者单位 | 1.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Ctr Opt Imagery Anal & Learning, Xian 710119, Shaanxi, Peoples R China; 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
推荐引用方式 GB/T 7714 | Yuan, Yuan,Tian, Chunlin,Lu, Xiaoqiang. Auxiliary Loss Multimodal GRU Model in Audio-Visual Speech Recognition[J]. IEEE ACCESS,2018,6:5573-5583. |
APA | Yuan, Yuan,Tian, Chunlin,&Lu, Xiaoqiang.(2018).Auxiliary Loss Multimodal GRU Model in Audio-Visual Speech Recognition.IEEE ACCESS,6,5573-5583. |
MLA | Yuan, Yuan,et al."Auxiliary Loss Multimodal GRU Model in Audio-Visual Speech Recognition".IEEE ACCESS 6(2018):5573-5583. |
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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 | ||
Auxiliary Loss Multi(1638KB) | 期刊论文 | 出版稿 | 限制开放 | CC BY-NC-SA | 请求全文 |
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