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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 6 of 6 1 Oriental Language Recognition (OLR) 2020: Summary and Analysis ... Li, Jing; Wang, Binling; Zhi, Yiming. - : arXiv, 2021 BASE Show details 2 OLR 2021 Challenge: Datasets, Rules and Baselines ... Wang, Binling; Hu, Wenxuan; Li, Jing. - : arXiv, 2021 BASE Show details 3 Visual-aware Attention Dual-stream Decoder for Video Captioning ... Sun, Zhixin; Zhong, Xian; Chen, Shuqin. - : arXiv, 2021 BASE Show details 4 Additive Phoneme-aware Margin Softmax Loss for Language Recognition ... Li, Zheng; Liu, Yan; Li, Lin; Hong, Qingyang. - : arXiv, 2021 Abstract: This paper proposes an additive phoneme-aware margin softmax (APM-Softmax) loss to train the multi-task learning network with phonetic information for language recognition. In additive margin softmax (AM-Softmax) loss, the margin is set as a constant during the entire training for all training samples, and that is a suboptimal method since the recognition difficulty varies in training samples. In additive angular margin softmax (AAM-Softmax) loss, the additional angular margin is set as a costant as well. In this paper, we propose an APM-Softmax loss for language recognition with phoneitc multi-task learning, in which the additive phoneme-aware margin is automatically tuned for different training samples. More specifically, the margin of language recognition is adjusted according to the results of phoneme recognition. Experiments are reported on Oriental Language Recognition (OLR) datasets, and the proposed method improves AM-Softmax loss and AAM-Softmax loss in different language recognition testing ... : Accepted by Interspeech 2021 ... Keyword: Audio and Speech Processing eess.AS; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Sound cs.SD URL: https://arxiv.org/abs/2106.12851 https://dx.doi.org/10.48550/arxiv.2106.12851 BASE Hide details 5 An Integrated Framework for Two-pass Personalized Voice Trigger ... Liao, Dexin; Li, Jing; Zhi, Yiming. - : arXiv, 2021 BASE Show details 6 AP20-OLR Challenge: Three Tasks and Their Baselines ... Li, Zheng; Zhao, Miao; Hong, Qingyang. - : arXiv, 2020 BASE Show details

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