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We present a number of low-resource approaches to the tasks of the ZeroResource Speech Challenge 2021. We build on the unsupervised representations ofspeech proposed by the organizers as a baseline, derived from CPC and clusteredwith the k-means algorithm. We demonstrate that simple methods of refiningthose representations can narrow the gap, or even improve upon the solutionswhich use a high computational budget. The results lead to the conclusion thatthe CPC-derived representations are still too noisy for training languagemodels, but stable enough for simpler forms of pattern matching and retrieval.

Information Retrieval for ZeroSpeech 2021: The Submission by University of Wroclaw