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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 Page: 1 2 3 4 5...9 Hits 1 – 20 of 175 1 Deep Neural Convolutive Matrix Factorization for Articulatory Representation Decomposition ... Lian, Jiachen; Black, Alan W; Goldstein, Louis. - : arXiv, 2022 BASE Show details 2 Cross-Lingual Text-to-Speech Using Multi-Task Learning and Speaker Classifier Joint Training ... Yang, J.; He, Lei. - : arXiv, 2022 BASE Show details 3 BEA-Base: A Benchmark for ASR of Spontaneous Hungarian ... Mihajlik, P.; Balog, A.; Gráczi, T. E.. - : arXiv, 2022 BASE Show details 4 Improving the fusion of acoustic and text representations in RNN-T ... Zhang, Chao; Li, Bo; Lu, Zhiyun; Sainath, Tara N.; Chang, Shuo-yiin. - : arXiv, 2022 Abstract: The recurrent neural network transducer (RNN-T) has recently become the mainstream end-to-end approach for streaming automatic speech recognition (ASR). To estimate the output distributions over subword units, RNN-T uses a fully connected layer as the joint network to fuse the acoustic representations extracted using the acoustic encoder with the text representations obtained using the prediction network based on the previous subword units. In this paper, we propose to use gating, bilinear pooling, and a combination of them in the joint network to produce more expressive representations to feed into the output layer. A regularisation method is also proposed to enable better acoustic encoder training by reducing the gradients back-propagated into the prediction network at the beginning of RNN-T training. Experimental results on a multilingual ASR setting for voice search over nine languages show that the joint use of the proposed methods can result in 4%--5% relative word error rate reductions with only a few ... : Paper to appear at ICASSP 2022 ... Keyword: Artificial Intelligence cs.AI; Audio and Speech Processing eess.AS; Computation and Language cs.CL; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Sound cs.SD URL: https://dx.doi.org/10.48550/arxiv.2201.10240 https://arxiv.org/abs/2201.10240 BASE Hide details 5 Cross-view Brain Decoding ... Oota, Subba Reddy; Arora, Jashn; Gupta, Manish. - : arXiv, 2022 BASE Show details 6 Automatic Depression Detection: An Emotional Audio-Textual Corpus and a GRU/BiLSTM-based Model ... Shen, Ying; Yang, Huiyu; Lin, Lin. - : arXiv, 2022 BASE Show details 7 Learning English with Peppa Pig ... Nikolaus, Mitja; Alishahi, Afra; Chrupała, Grzegorz. - : arXiv, 2022 BASE Show details 8 Separate What You Describe: Language-Queried Audio Source Separation ... Liu, Xubo; Liu, Haohe; Kong, Qiuqiang. - : arXiv, 2022 BASE Show details 9 Chain-based Discriminative Autoencoders for Speech Recognition ... Lee, Hung-Shin; Huang, Pin-Tuan; Cheng, Yao-Fei. - : arXiv, 2022 BASE Show details 10 Unsupervised word-level prosody tagging for controllable speech synthesis ... Guo, Yiwei; Du, Chenpeng; Yu, Kai. - : arXiv, 2022 BASE Show details 11 gTLO: A Generalized and Non-linear Multi-Objective Deep Reinforcement Learning Approach ... Dornheim, Johannes. - : arXiv, 2022 BASE Show details 12 Cetacean Translation Initiative: a roadmap to deciphering the communication of sperm whales ... Andreas, Jacob; Beguš, Gašper; Bronstein, Michael M.. - : arXiv, 2021 BASE Show details 13 Improving End-To-End Modeling for Mispronunciation Detection with Effective Augmentation Mechanisms ... Lo, Tien-Hong; Sung, Yao-Ting; Chen, Berlin. - : arXiv, 2021 BASE Show details 14 An Improved StarGAN for Emotional Voice Conversion: Enhancing Voice Quality and Data Augmentation ... He, Xiangheng; Chen, Junjie; Rizos, Georgios. - : arXiv, 2021 BASE Show details 15 NVC-Net: End-to-End Adversarial Voice Conversion ... Nguyen, Bac; Cardinaux, Fabien. - : arXiv, 2021 BASE Show details 16 Speech2Slot: An End-to-End Knowledge-based Slot Filling from Speech ... Wang, Pengwei; Ye, Xin; Zhou, Xiaohuan. - : arXiv, 2021 BASE Show details 17 NIST SRE CTS Superset: A large-scale dataset for telephony speaker recognition ... Sadjadi, Seyed Omid. - : arXiv, 2021 BASE Show details 18 Interpreting intermediate convolutional layers of CNNs trained on raw speech ... Beguš, Gašper; Zhou, Alan. - : arXiv, 2021 BASE Show details 19 A multispeaker dataset of raw and reconstructed speech production real-time MRI video and 3D volumetric images ... Yongwan Lim; Toutios, Asterios; Bliesener, Yannick. - : figshare, 2021 BASE Show details 20 A multispeaker dataset of raw and reconstructed speech production real-time MRI video and 3D volumetric images ... Yongwan Lim; Toutios, Asterios; Bliesener, Yannick. - : figshare, 2021 BASE Show details Page: 1 2 3 4 5...9

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