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A central assumption in the perceptual attunement literature holds that exposure to a speech sound contrast leads to improvement in native speech sound processing. However, whether the amount of exposure matters for this process has not been put to a direct test. We elucidated indicators of frequency‐dependent perceptual attunement by comparing 5–8‐month‐old Dutch infants’ discrimination of tokens...
Recent work has explored deep architectures for learning acoustic features in an unsupervised or weakly-supervised way for phone recognition. Here we investigate the role of the input features, and in particular we test whether standard mel-scaled filterbanks could be replaced by inherently richer representations, such as derived from an analytic scattering spectrum. We use a Siamese network using...
This paper reports on the results of the Zero Resource Speech Challenge 2015, the first unified benchmark for zero resource speech technology, which aims at the unsupervised discovery of subword and word units from raw speech. This paper discusses the motivation for the challenge, its data sets, tasks and baseline systems. We outline the ideas behind the systems that were submitted for the two challenge...
In this paper we investigate a computational model of word learning, that is embedded in a cognitively and ecologically plausible framework. Multi-modal stimuli from four different speakers form a varied source of experience. The model incorporates active learning, attention to a communicative setting and clarity of the visual scene. The model's ability to learn associations between speech utterances...
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