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Pre-training on high-resource speech recognition improves low-resource speech-to-text translation., , , , и . NAACL-HLT (1), стр. 58-68. Association for Computational Linguistics, (2019)Analyzing ASR Pretraining for Low-Resource Speech-to-Text Translation., , и . ICASSP, стр. 7909-7913. IEEE, (2020)Unsupervised neural network based feature extraction using weak top-down constraints., , , и . ICASSP, стр. 5818-5822. IEEE, (2015)Semantic Parsing with Bayesian Tree Transducers., , и . ACL (1), стр. 488-496. The Association for Computer Linguistics, (2012)Which Words Are Hard to Recognize? Prosodic, Lexical, and Disfluency Factors that Increase ASR Error Rates., , и . ACL, стр. 380-388. The Association for Computer Linguistics, (2008)Modeling Graph Languages with Grammars Extracted via Tree Decompositions., , и . FSMNLP, стр. 54-62. The Association for Computer Linguistics, (2013)A Joint Learning Model of Word Segmentation, Lexical Acquisition, and Phonetic Variability., , , и . EMNLP, стр. 42-54. ACL, (2013)Unsupervised NLP and Human Language Acquisition: Making Connections to Make Progress.. ULNLP@EMNLP, стр. 1. Association for Computational Linguistics, (2011)Representational Bias in Unsupervised Learning of Syllable Structure., и . CoNLL, стр. 112-119. ACL, (2005)Evaluating computational models of infant phonetic learning across languages., , , , и . CogSci, cognitivesciencesociety.org, (2020)