Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
485437 | Procedia Computer Science | 2016 | 6 Pages |
Abstract
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 tracks: unsupervised subword unit modeling and spoken term discovery, and summarize their results. The results obtained by participating teams show great promise; many systems beat the provided baselines and some even perform better than comparable supervised systems.
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Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Maarten Versteegh, Xavier Anguera, Aren Jansen, Emmanuel Dupoux,