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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. - : arXiv, 2022 BASE Show 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 Abstract: This document provides a brief description of the National Institute of Standards and Technology (NIST) speaker recognition evaluation (SRE) conversational telephone speech (CTS) Superset. The CTS Superset has been created in an attempt to provide the research community with a large-scale dataset along with uniform metadata that can be used to effectively train and develop telephony (narrowband) speaker recognition systems. It contains a large number of telephony speech segments from more than 6800 speakers with speech durations distributed uniformly in the [10s, 60s] range. The segments have been extracted from the source corpora used to compile prior SRE datasets (SRE1996-2012), including the Greybeard corpus as well as the Switchboard and Mixer series collected by the Linguistic Data Consortium (LDC). In addition to the brief description, we also report speaker recognition results on the NIST 2020 CTS Speaker Recognition Challenge, obtained using a system trained with the CTS Superset. The results will ... Keyword: Artificial Intelligence cs.AI; Audio and Speech Processing eess.AS; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Machine Learning stat.ML; Sound cs.SD URL: https://dx.doi.org/10.48550/arxiv.2108.07118 https://arxiv.org/abs/2108.07118 BASE Hide 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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