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Subspace-based Representation and Learning for Phonotactic Spoken Language Recognition ...
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
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2
Multilingual and Multimodal Abuse Detection ...
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3
WavThruVec: Latent speech representation as intermediate features for neural speech synthesis ...
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Fine-grained Noise Control for Multispeaker Speech Synthesis ...
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5
Emotion Intensity and its Control for Emotional Voice Conversion ...
Zhou, Kun; Sisman, Berrak; Rana, Rajib. - : arXiv, 2022
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Low-dimensional representation of infant and adult vocalization acoustics ...
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Chain-based Discriminative Autoencoders for Speech Recognition ...
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Filter-based Discriminative Autoencoders for Children Speech Recognition ...
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Self-Supervised Representation Learning for Speech Using Visual Grounding and Masked Language Modeling ...
Peng, Puyuan; Harwath, David. - : arXiv, 2022
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10
Continual Learning for Monolingual End-to-End Automatic Speech Recognition ...
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Cetacean Translation Initiative: a roadmap to deciphering the communication of sperm whales ...
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Speech Representations and Phoneme Classification for Preserving the Endangered Language of Ladin ...
Durante, Zane; Mathur, Leena; Ye, Eric. - : arXiv, 2021
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13
Applying Phonological Features in Multilingual Text-To-Speech ...
Zhang, Cong; Zeng, Huinan; Liu, Huang. - : arXiv, 2021
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14
English Accent Accuracy Analysis in a State-of-the-Art Automatic Speech Recognition System ...
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Cross-lingual Low Resource Speaker Adaptation Using Phonological Features ...
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Arabic Speech Recognition by End-to-End, Modular Systems and Human ...
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The INTERSPEECH 2021 Computational Paralinguistics Challenge: COVID-19 Cough, COVID-19 Speech, Escalation & Primates ...
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Discrete representations in neural models of spoken language ...
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19
Phrase break prediction with bidirectional encoder representations in Japanese text-to-speech synthesis ...
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20
Learning De-identified Representations of Prosody from Raw Audio ...
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