The zero resource speech challenge 2015

By Maarten Versteegh, Roland Thiollière, Thomas Schatz, Xuan-Nga Cao, Xavier Anguera Miró, Aren Jansen, Emmanuel Dupoux. 2015

107 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Evaluation & Benchmarks, Speech & Audio

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Citations in the corpus

Learning Hierarchical Discrete Linguistic Units from Visually-Grounded Speech (2019, background): “ metrics Learning unsupervised speech representations that are indicative of phonetic content is of high interest to the speech community, and recently has been the focus of the ZeroSpeech Challenge (Versteegh et al., 2015; Dunbar et al., 2017; 2019). One of the core evaluations is the model-free, m”
The zero resource speech challenge 2017 (2017, methodology): “As the previous Zero Resource Speech Challenge [10, 11], the 2017 installment consists of two different sub-challenges.”
A segmental framework for fully-unsupervised large-vocabulary speech recognition (2016, methodology): “The baseline provided as part of the lexical discovery track of the Zero Resource Speech Challenge 2015 (ZRS) [8] is a UTD system based on the earlier work of [18].”
Self-Supervised Speech Representation Learning: A Review (2022, background): “The relation between model sizes and downstream performances have also been investigated [278], [279].”
Measuring the perceptual availability of phonological features during language acquisition using unsupervised binary stochastic autoencoders (2019, methodology): “Data selection criteria and annotation procedures are are described in more detail in Versteegh et al. (2015).”
Early phonetic learning without phonetic categories: Insights from large-scale simulations on realistic input (2021, methodology): “training language, outperforming a number of alternatives that have been proposed for unsupervised speech representation learning (57, 58, 68).”
Cyclic Spectral Modeling for Unsupervised Unit Discovery into Voice Conversion with Excitation and Waveform Modeling (2020, background): “Notably, in 2015 [4, 5], 2017 [7], and 2019 [10], the Zero Resource Speech Challenge (ZSC) has been organized, where the objective is to perform the discovery of subword/wordlike speech units (speech sounds representations) without any textual annotations, i.”