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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...38 Hits 1 – 20 of 752 1 A comparative study of several parameterizations for speaker recognition ... Faundez-Zanuy, Marcos. - : arXiv, 2022 BASE Show details 2 Speaker verification in mismatch training and testing conditions ... Faundez-Zanuy, Marcos; Slupinski, Adam. - : arXiv, 2022 BASE Show details 3 Speech Segmentation Optimization using Segmented Bilingual Speech Corpus for End-to-end Speech Translation ... Fukuda, Ryo; Sudoh, Katsuhito; Nakamura, Satoshi. - : arXiv, 2022 BASE Show details 4 A New Amharic Speech Emotion Dataset and Classification Benchmark ... Retta, Ephrem A.; Almekhlafi, Eiad; Sutcliffe, Richard. - : arXiv, 2022 BASE Show details 5 The Norwegian Parliamentary Speech Corpus ... Solberg, Per Erik; Ortiz, Pablo. - : arXiv, 2022 BASE Show details 6 Subspace-based Representation and Learning for Phonotactic Spoken Language Recognition ... Lee, Hung-Shin; Tsao, Yu; Jeng, Shyh-Kang; Wang, Hsin-Min. - : arXiv, 2022 Abstract: Phonotactic constraints can be employed to distinguish languages by representing a speech utterance as a multinomial distribution or phone events. In the present study, we propose a new learning mechanism based on subspace-based representation, which can extract concealed phonotactic structures from utterances, for language verification and dialect/accent identification. The framework mainly involves two successive parts. The first part involves subspace construction. Specifically, it decodes each utterance into a sequence of vectors filled with phone-posteriors and transforms the vector sequence into a linear orthogonal subspace based on low-rank matrix factorization or dynamic linear modeling. The second part involves subspace learning based on kernel machines, such as support vector machines and the newly developed subspace-based neural networks (SNNs). The input layer of SNNs is specifically designed for the sample represented by subspaces. The topology ensures that the same output can be derived from ... : Published in IEEE/ACM Trans. Audio, Speech, Lang. Process., 2020, vol. 28, pp. 3065-3079 ... Keyword: Audio and Speech Processing eess.AS; Computation and Language cs.CL; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Machine Learning cs.LG; Sound cs.SD URL: https://dx.doi.org/10.48550/arxiv.2203.15576 https://arxiv.org/abs/2203.15576 BASE Hide details 7 LPC Augment: An LPC-Based ASR Data Augmentation Algorithm for Low and Zero-Resource Children's Dialects ... Johnson, Alexander; Fan, Ruchao; Morris, Robin. - : arXiv, 2022 BASE Show details 8 Automatic Dialect Density Estimation for African American English ... Johnson, Alexander; Everson, Kevin; Ravi, Vijay. - : arXiv, 2022 BASE Show details 9 End-to-end contextual asr based on posterior distribution adaptation for hybrid ctc/attention system ... Zhang, Zhengyi; Zhou, Pan. - : arXiv, 2022 BASE Show details 10 Towards Contextual Spelling Correction for Customization of End-to-end Speech Recognition Systems ... Wang, Xiaoqiang; Liu, Yanqing; Li, Jinyu. - : arXiv, 2022 BASE Show details 11 SHAS: Approaching optimal Segmentation for End-to-End Speech Translation ... Tsiamas, Ioannis; Gállego, Gerard I.; Fonollosa, José A. R.. - : arXiv, 2022 BASE Show details 12 Automatic Detection of Speech Sound Disorder in Child Speech Using Posterior-based Speaker Representations ... Ng, Si-Ioi; Ng, Cymie Wing-Yee; Wang, Jiarui. - : arXiv, 2022 BASE Show details 13 Towards a Perceptual Model for Estimating the Quality of Visual Speech ... Aldeneh, Zakaria; Fedzechkina, Masha; Seto, Skyler. - : arXiv, 2022 BASE Show details 14 Learning and controlling the source-filter representation of speech with a variational autoencoder ... Sadok, Samir; Leglaive, Simon; Girin, Laurent. - : arXiv, 2022 BASE Show details 15 Repeat after me: Self-supervised learning of acoustic-to-articulatory mapping by vocal imitation ... Georges, Marc-Antoine; Diard, Julien; Girin, Laurent. - : arXiv, 2022 BASE Show details 16 Can Social Robots Effectively Elicit Curiosity in STEM Topics from K-1 Students During Oral Assessments? ... Johnson, Alexander; Martin, Alejandra; Quintero, Marlen. - : arXiv, 2022 BASE Show details 17 Expression-preserving face frontalization improves visually assisted speech processing ... Kang, Zhiqi; Sadeghi, Mostafa; Horaud, Radu. - : arXiv, 2022 BASE Show details 18 Synthesizing Dysarthric Speech Using Multi-talker TTS for Dysarthric Speech Recognition ... Soleymanpour, Mohammad; Johnson, Michael T.; Soleymanpour, Rahim. - : arXiv, 2022 BASE Show details 19 A Hierarchical Model for Spoken Language Recognition ... Ferrer, Luciana; Castan, Diego; McLaren, Mitchell. - : arXiv, 2022 BASE Show details 20 Language vs Speaker Change: A Comparative Study ... Mishra, Jagabandhu; Prasanna, S. R. Mahadeva. - : arXiv, 2022 BASE Show details Page: 1 2 3 4 5...38

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