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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 – 10 of 10 1 DARTS-ASR: Differentiable Architecture Search for Multilingual Speech Recognition and Adaptation ... Chen, Yi-Chen; Hsu, Jui-Yang; Lee, Cheng-Kuang. - : arXiv, 2020 BASE Show details 2 From Semi-supervised to Almost-unsupervised Speech Recognition with Very-low Resource by Jointly Learning Phonetic Structures from Audio and Text Embeddings ... Chen, Yi-Chen; Huang, Sung-Feng; Lee, Hung-yi. - : arXiv, 2019 BASE Show details 3 Almost-unsupervised Speech Recognition with Close-to-zero Resource Based on Phonetic Structures Learned from Very Small Unpaired Speech and Text Data ... Chen, Yi-Chen; Shen, Chia-Hao; Huang, Sung-Feng. - : arXiv, 2018 BASE Show details 4 Phonetic-and-Semantic Embedding of Spoken Words with Applications in Spoken Content Retrieval ... Chen, Yi-Chen; Huang, Sung-Feng; Shen, Chia-Hao. - : arXiv, 2018 BASE Show details 5 Towards Unsupervised Automatic Speech Recognition Trained by Unaligned Speech and Text only ... Chen, Yi-Chen; Shen, Chia-Hao; Huang, Sung-Feng. - : arXiv, 2018 BASE Show details 6 Improved Audio Embeddings by Adjacency-Based Clustering with Applications in Spoken Term Detection ... Huang, Sung-Feng; Chen, Yi-Chen; Lee, Hung-yi; Lee, Lin-shan. - : arXiv, 2018 Abstract: Embedding audio signal segments into vectors with fixed dimensionality is attractive because all following processing will be easier and more efficient, for example modeling, classifying or indexing. Audio Word2Vec previously proposed was shown to be able to represent audio segments for spoken words as such vectors carrying information about the phonetic structures of the signal segments. However, each linguistic unit (word, syllable, phoneme in text form) corresponds to unlimited number of audio segments with vector representations inevitably spread over the embedding space, which causes some confusion. It is therefore desired to better cluster the audio embeddings such that those corresponding to the same linguistic unit can be more compactly distributed. In this paper, inspired by Siamese networks, we propose some approaches to achieve the above goal. This includes identifying positive and negative pairs from unlabeled data for Siamese style training, disentangling acoustic factors such as speaker ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.1811.02775 https://arxiv.org/abs/1811.02775 BASE Hide details 7 EFL learners' awareness of metonymy-metaphor continuum in figurative expressions Lai, Huei-ling; Chen, Yi-chen In: Language awareness. - Abingdon : Routledge 21 (2012) 3, 235-248 BLLDB OLC Linguistik Show details 8 Evolution of eukaryal tRNA-guanine transglycosylase: insight gained from the heterocyclic substrate recognition by the wild-type and mutant human and Escherichia coli tRNA-guanine transglycosylases Chen, Yi-Chen; Brooks, Allen F.; Goodenough-Lashua, DeeAnne M.. - : Oxford University Press, 2011 BASE Show details 9 Characterization of the human tRNA-guanine transglycosylase: Confirmation of the heterodimeric subunit structure Chen, Yi-Chen; Kelly, Vincent P.; Stachura, Stefanie V.. - : Cold Spring Harbor Laboratory Press, 2010 BASE Show details 10 Evolution of Eukaryal tRNA-Guanine Transglycosylase: Insight Gained from the Characterization of the Human and Escherichia coli tRNA-Guanine Transglycosylases. Chen, Yi-Chen BASE Show details

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