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A comparison of neural network methods for unsupervised representation learning on the zero resource speech challenge

, , , and . Sixteenth Annual Conference of the International Speech Communication Association, (2015)

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Unsupervised Dependency Parsing with Acoustic Cues., and . TACL, (2013)Pre-training on high-resource speech recognition improves low-resource speech-to-text translation., , , , and . NAACL-HLT (1), page 58-68. Association for Computational Linguistics, (2019)Modeling Graph Languages with Grammars Extracted via Tree Decompositions., , and . FSMNLP, page 54-62. The Association for Computer Linguistics, (2013)A Joint Learning Model of Word Segmentation, Lexical Acquisition, and Phonetic Variability., , , and . EMNLP, page 42-54. ACL, (2013)Lexical Generalization in CCG Grammar Induction for Semantic Parsing., , , and . EMNLP, page 1512-1523. ACL, (2011)Unsupervised NLP and Human Language Acquisition: Making Connections to Make Progress.. ULNLP@EMNLP, page 1. Association for Computational Linguistics, (2011)Representational Bias in Unsupervised Learning of Syllable Structure., and . CoNLL, page 112-119. ACL, (2005)Which Words Are Hard to Recognize? Prosodic, Lexical, and Disfluency Factors that Increase ASR Error Rates., , and . ACL, page 380-388. The Association for Computer Linguistics, (2008)Semantic Parsing with Bayesian Tree Transducers., , and . ACL (1), page 488-496. The Association for Computer Linguistics, (2012)Classifying topics in speech when all you have is crummy translations., , , and . CoRR, (2019)